Sources of Carotenoids in Amazonian Fruits.
Orquídea Vasconcelos Dos SantosRosely Carvalho do RosárioBarbara Elisabeth Teixeira-CostaPublished in: Molecules (Basel, Switzerland) (2024)
Epidemiological studies have shown that a diet rich in bioactive components significantly reduces cardiovascular disease incidence and mortality. In this sense, there is a need for meta-analytical research that confirms this phenomenon and increases specific knowledge about certain bioactive compounds such as carotenoids. Thus, this systematic review and meta-analysis aim to disseminate knowledge about the sources of carotenoids in fruit consumed in the north of Brazil which are outside the Brazilian trade balance. A systematic review and a meta-analysis following the PRISMA guidelines were conducted based on a random effects synthesis of multivariable-adjusted relative risks (RRs). Searches of seven sources were carried out, including PubMed, Science Direct from Elsevier, Web of Science, Scielo, Eric Research and Google Scholar databases. The systematic review was guided by a systematic review protocol based on the POT strategy (population, outcome and type of study) adapted for use in this research. Mendeley was a resource used to organize and manage references and exclude duplicates of studies selected for review. In this review, we present the potential bioactive compounds concentrated in little-known fruit species from the Amazon and their benefits. Consuming fruits that are rich in notable constituents such as carotenoids is important for the prevention of chronic non-communicable diseases through anti-inflammatory and anticoagulant properties, as well as antivirals, immunomodulators and antioxidants agents that directly affect the immune response.
Keyphrases
- systematic review
- cardiovascular disease
- drinking water
- immune response
- meta analyses
- healthcare
- public health
- anti inflammatory
- risk factors
- case control
- human health
- cardiovascular events
- venous thromboembolism
- physical activity
- type diabetes
- atrial fibrillation
- randomized controlled trial
- big data
- risk assessment
- tertiary care
- inflammatory response
- machine learning
- climate change
- deep learning
- coronary artery disease