Impact of fiber-fortified food consumption on anthropometric measurements and cardiometabolic outcomes: A systematic review, meta-analyses, and meta-regressions of randomized controlled trials.
Delia Pei Shan LeeAiwei PengFransisca TaniasuriDenise TanJung Eun KimPublished in: Critical reviews in food science and nutrition (2022)
The consumption of processed and refined food lacking in fiber has led to global prevalence of obesity and cardiometabolic diseases. Fiber-fortification into these foods can yield potential health improvements to reduce disease risk. This meta-analyses aimed to evaluate how fiber-fortified food consumption changes body composition, blood pressure, blood lipid-lipoprotein panel, and glycemic-related markers. Searches were performed from 5 databases, with 31 randomized controlled trial eventually analyzed. Hedges' g values (95% confidence interval [CI]) attained from outcome change values were calculated using random-effects model. Fiber-fortified food significantly reduced body weight (-0.31 [-0.59, -0.03]), fat mass (-0.49 [-0.72, -0.26]), total cholesterol (-0.54 [-0.71, -0.36]), low-density lipoprotein cholesterol (-0.49 [-0.65, -0.33]), triglycerides (-0.24 [-0.36, -0.12]), fasting glucose (-0.30 [-0.49, -0.12]), and HbA1c (-0.44 [-0.74, -0.13]). Subgroup analysis differentiated soluble fiber as significantly reducing triglycerides and insulin while insoluble fiber significantly reduced body weight, BMI, and HbA1c. Greater outcome improvements were observed with solid/semi-solid food state than liquid state. Additionally, fiber fortification of <15 g/day induced more health outcome benefits compared to ≥15 g/day, although meta-regression found a dose-dependent improvement to waist circumference ( p -value = 0.036). Findings from this study suggest that consuming food fortified with dietary fiber can improve anthropometric and cardiometabolic outcomes.
Keyphrases
- body weight
- body composition
- randomized controlled trial
- human health
- blood pressure
- healthcare
- meta analyses
- systematic review
- body mass index
- type diabetes
- risk assessment
- machine learning
- clinical trial
- insulin resistance
- risk factors
- physical activity
- resistance training
- weight loss
- skeletal muscle
- oxidative stress
- heart rate
- big data
- drug induced
- high glucose