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Large observational studies find that people who eat more ultra-processed food tend to have higher rates of several diseases and of death from any cause. A 2026 analysis pooling 51 prospective cohorts reported these associations across nearly 8.82 million adults. The findings describe patterns across populations; they do not prove that ultra-processed foods caused an individual’s illness or predict any one person’s absolute risk.
What counts as ultra-processed food in these studies?
The studies generally classified foods using NOVA, a system that groups foods by the extent and purpose of their processing. Ultra-processed foods (UPFs) are a broad category, not a single nutritional profile: items within it can differ in ingredients and nutritional quality. The results therefore concern the category as measured in each study, not a finding that every product in it has the same health effect.
In the 2026 pooled analysis, participants’ diets were assessed using food-frequency questionnaires, 24-hour recalls, or dietary histories. The authors note that applying NOVA across different dietary instruments can lead to variation in how foods are classified. (Family Medicine and Community Health, 2026)
Which health outcomes were associated with higher intake?
The 2026 analysis combined 51 prospective cohorts involving 8,819,894 adults from the Americas, Europe, Asia, and Oceania. Follow-up ranged from 2 to 32 years. Higher UPF intake was associated with higher rates of cardiovascular events, cancer, overweight or obesity, metabolic syndrome or diabetes, depression or anxiety, digestive diseases, and all-cause mortality. (Family Medicine and Community Health, 2026)
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For all-cause mortality, the analysis reported a hazard ratio (HR) of 1.18 (95% confidence interval [CI] 1.10–1.26) when comparing the highest with the lowest intake categories. An HR compares the relative rate of an outcome over time between groups; 1.18 is not an 18-percentage-point increase in an individual’s chance of dying.
How do the reported estimates compare?
The studies used different exposure comparisons and evidence sets, so their estimates should not be treated as interchangeable. The table separates a highest-versus-lowest comparison from estimates for each additional 100 grams per day.
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| Analysis and comparison | Outcome | Reported estimate |
|---|---|---|
| 2026 pooled analysis; highest versus lowest intake | All-cause mortality | HR 1.18 (95% CI 1.10–1.26) |
| 2026 pooled analysis; each additional 100 g/day | All-cause mortality | HR 1.03 (95% CI 1.02–1.05) |
| 2026 pooled analysis; each additional 100 g/day | Cardiovascular events | HR 1.14 (95% CI 1.06–1.22) |
| 2026 pooled analysis; each additional 100 g/day | Cancer | HR 1.04 (95% CI 1.02–1.06) |
| 2026 pooled analysis; each additional 100 g/day | Metabolic syndrome or diabetes | HR 1.02 (95% CI 1.01–1.04) |
These are pooled observational dose-response estimates from the 2026 analysis. They describe the association estimated for each additional 100 g/day in the included studies, not a guaranteed change in risk for an individual.
Other mortality analyses provide context but use different study sets and exposure definitions:
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|---|---|---|
| 2025 mortality meta-analysis: 18 prospective studies, 1,148,387 participants and 173,107 deaths | Highest versus lowest intake: HR 1.15 (95% CI 1.09–1.22) | Substantial between-study heterogeneity (I²=83%) |
| 2025 mortality meta-analysis | Each 10% increment in UPF consumption: HR 1.10 (95% CI 1.04–1.16) | Substantial between-study heterogeneity (I²=91%) |
| 2024 BMJ prospective cohort | Highest versus lowest quarter of intake: HR 1.04 (95% CI 1.01–1.07) | A single cohort result, not a pooled estimate |
The 2025 review’s heterogeneity statistics indicate that results varied considerably among studies. Its search covered studies through 2 July 2024. The cohort estimate is likewise not directly comparable with pooled estimates, which combine different populations and exposure definitions. Sources: Systematic Reviews, 2025; The BMJ, 2024.
How strong is the evidence?
Prospective cohorts measure intake before later health outcomes, which helps establish that exposure preceded the outcome. They are still observational studies, not randomized trials. Differences in other health or lifestyle factors, errors in measuring diet, changes in eating habits during follow-up, and variation between populations can influence the estimated associations.
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The 2026 analysis rated the evidence low certainty for cardiovascular events, cancer, metabolic syndrome or diabetes, depression or anxiety, digestive diseases, and all-cause mortality; it rated evidence moderate for overweight or obesity and very low for hypertension. These ratings apply to that review’s evaluation of its included evidence. (Family Medicine and Community Health, 2026)
Reviewers can reach different evidence classifications because they assess different studies, define outcomes differently, and use different grading methods. For example, a 2024 BMJ umbrella review classified evidence for cardiovascular disease-related mortality as convincing under its own criteria, while rating its GRADE certainty very low; for dose-response type 2 diabetes, it reported moderate GRADE certainty. A separate 2024 Clinical Nutrition umbrella review identified 39 meta-analyses and updated them with 122 individual articles across 49 outcomes; its strongest classifications were convincing evidence for renal function decline and wheezing in children and adolescents. These conclusions refer to the respective reviews, not to a single universal ranking of UPF evidence. (The BMJ, 2024; Clinical Nutrition, 2024)
What these results can—and cannot—tell an individual
The estimates describe relative differences between groups or exposure levels in the studies. They do not provide a reader’s baseline probability of developing a disease, an absolute increase in that probability, or a personal forecast. Absolute risk depends on a person’s circumstances and on the specific outcome and timeframe being considered.
The findings also do not show that reducing a particular food, following a named diet, or using a specific product will prevent disease. The studies assess population-level associations with a broad dietary category; they do not test a particular intervention.
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