Dietary Intake and Arterial Stiffness in Children and Adolescents: A Systematic Review.
Allanah LeedEmma SheridanBrooke BakerSara BamfordElana EmmanouilidisFletcher StewartKristen OstafeMustafa SarwariKaren LimMiaobing ZhengSheikh Mohammed Shariful IslamKristy A BoltonCarley Ann GrimesPublished in: Nutrients (2023)
Arterial stiffness is a risk factor for cardiovascular disease that is affected by diet. However, research understanding how these dietary risk factors are related to arterial stiffness during childhood is limited. The purpose of this review was to determine whether various dietary factors were associated with arterial stiffness in the pediatric population. Five databases were systematically searched. Intervention studies, cross-sectional and cohort studies were included that investigated nutrient or food intake and outcomes of arterial stiffness, primarily measured by pulse wave velocity (PWV) and augmentation index (AIx), in the pediatric population (aged 0-18 years). A final 19 studies (six intervention and 13 observational) were included. Only two intervention studies, including a vitamin D and omega-3 supplementation trial, found protective effects on PWV and AIx in adolescents. Findings from observational studies were overall inconsistent and varied. There was limited evidence to indicate a protective effect of a healthy dietary pattern on arterial stiffness and an adverse effect of total fat intake, sodium intake and fast-food consumption. Overall, results indicated that some dietary factors may be associated with arterial stiffness in pediatric populations; however, inconsistencies were observed across all study designs. Further longitudinal and intervention studies are warranted to confirm the potential associations found in this review.
Keyphrases
- blood pressure
- randomized controlled trial
- cross sectional
- cardiovascular disease
- risk factors
- case control
- type diabetes
- study protocol
- clinical trial
- young adults
- risk assessment
- metabolic syndrome
- skeletal muscle
- machine learning
- weight gain
- deep learning
- human health
- high resolution
- insulin resistance
- big data
- single molecule
- cardiovascular events
- drug induced