Impact of the consumption of ultra-processed foods on children, adolescents and adults' health: scope review.
Maria Laura da Costa LouzadaCaroline Dos Santos CostaThays Nascimento SouzaGabriela Lopes da CruzRenata Bertazzi LevyCarlos Augusto MonteiroPublished in: Cadernos de saude publica (2022)
The aim of this study was to conduct a literature scope review of the association between the consumption of ultra-processed foods and health outcomes. The search was carried out in the PubMed, Web of Science and LILACS databases. Studies that assessed the association between the consumption of ultra-processed foods, identified on the NOVA classification, and health outcomes were eligible. The review process resulted in the selection of 63 studies, which were analyzed in terms of quality using a tool from the National Institutes of Health. The outcomes found included obesity, metabolic risk markers, diabetes, cardiovascular diseases, cancer, asthma, depression, frailty, gastrointestinal diseases and mortality indicators. The evidence was particularly consistent for obesity (or indicators related to it) in adults, whose association with the consumption of ultra-processed foods was demonstrated, with dose-response effect, in cross-sectional studies with representative samples from five countries, in four large cohort studies and in a randomized clinical trial. Large cohort studies have also found a significant association between the consumption of ultra-processed foods and the risk of cardiovascular diseases, diabetes and cancer - even after adjusting for obesity. Two cohort studies have shown an association of ultra-processed foods consumption with depression and four cohort studies with all-cause mortality. This review summarized the studies' results that described the association between the consumption of ultra-processed foods and various non-communicable diseases and their risk factors, which has important implications for public health.
Keyphrases
- public health
- cardiovascular disease
- high resolution
- type diabetes
- risk factors
- insulin resistance
- metabolic syndrome
- cross sectional
- weight loss
- healthcare
- young adults
- case control
- systematic review
- mental health
- depressive symptoms
- chronic obstructive pulmonary disease
- papillary thyroid
- machine learning
- weight gain
- glycemic control
- squamous cell carcinoma
- deep learning
- physical activity
- coronary artery disease
- squamous cell
- mass spectrometry
- cystic fibrosis
- lung function
- sleep quality
- climate change
- artificial intelligence
- allergic rhinitis