Current Insights into Monitoring, Bioaccumulation, and Potential Health Effects of Microplastics Present in the Food Chain.
Leonard W D van RaamsdonkMeike van der ZandeAlbert A KoelmansRon L A P HoogenboomRuud J B PetersMaria J GrootAd A C M PeijnenburgYannick J A WeesepoelPublished in: Foods (Basel, Switzerland) (2020)
Microplastics (MPs) are considered an emerging issue as environmental pollutants and a potential health threat. This review will focus on recently published data on concentrations in food, possible effects, and monitoring methods. Some data are available on concentrations in seafood (fish, bivalves, and shrimps), water, sugar, salt, and honey, but are lacking for other foods. Bottled water is a considerable source with numbers varying between 2600 and 6300 MPs per liter. Particle size distributions have revealed an abundance of particles smaller than 25 µm, which are considered to have the highest probability to pass the intestinal border and to enter the systemic circulation of mammals. Some studies with mice and zebrafish with short- or medium-term exposure (up to 42 days) have revealed diverse results with respect to both the type and extent of effects. Most notable modifications have been observed in gut microbiota, lipid metabolism, and oxidative stress. The principal elements of MP monitoring in food are sample preparation, detection, and identification. Identified data gaps include a lack of occurrence data in plant- and animal-derived food, a need for more data on possible effects of different types of microplastics, a lack of in silico models, a lack of harmonized monitoring methods, and a further development of quality assurance.
Keyphrases
- human health
- risk assessment
- electronic health record
- big data
- oxidative stress
- healthcare
- heavy metals
- climate change
- systematic review
- public health
- type diabetes
- single cell
- dna damage
- preterm infants
- randomized controlled trial
- fatty acid
- ischemia reperfusion injury
- microbial community
- artificial intelligence
- deep learning
- mass spectrometry
- antibiotic resistance genes
- gestational age
- health risk assessment
- heat stress
- preterm birth
- sensitive detection
- health promotion
- plant growth
- quantum dots