医学
超重
科克伦图书馆
前瞻性队列研究
荟萃分析
体重增加
队列研究
置信区间
儿科
人口
随机对照试验
队列
梅德林
环境卫生
肥胖
内科学
体重
政治学
法学
作者
Ashleigh Reid,Bhupendrasinh F Chauhan,Rasheda Rabbani,Justin Lys,Leslie Copstein,Amrinder Singh Mann,Ahmed M Abou‐Setta,Michelle Fiander,Dylan MacKay,Jonathan McGavock,Brandy Wicklow,Ryan Zarychanski,Meghan B. Azad
出处
期刊:Pediatrics
[American Academy of Pediatrics]
日期:2016-03-01
卷期号:137 (3)
被引量:57
标识
DOI:10.1542/peds.2015-3603
摘要
Nonnutritive sweetener (NNS) consumption is increasing among children, yet its long-term health impact is unclear, particularly when exposure occurs during early life.To synthesize evidence from prospective studies evaluating the association of early-life NNS exposure and long-term metabolic health.Medline, Embase, and Cochrane Library (inception to July 2015).We aimed to include randomized controlled trials (RCTs) evaluating NNS-based interventions and prospective cohort studies reporting NNS exposure among pregnant women, infants, or children (<12 years of age), with a minimum study duration of 6 months.The primary outcome was BMI; secondary outcomes included growth velocity, overweight/obesity, adiposity, and adverse metabolic effects. Study quality and risk of bias were evaluated using validated assessment tools.We identified 6 eligible cohort studies and 2 RCTs (n = 15,641 children). Half of the cohorts reported increasing weight gain or fat mass accumulation with increasing NNS intake, and pooled data from 2 cohorts showed a significant correlation with BMI gain (weighted mean correlation 0.023, 95% confidence interval 0.006 to 0.041). RCTs reported contradictory effects on weight change in children receiving NNSs. No eligible studies evaluated prenatal or infant NNS exposure.Meta-analysis was limited because of the small number of eligible studies and heterogeneity of populations and outcomes.There is limited and inconsistent evidence of the long-term metabolic effects of NNS exposure during gestation, infancy, and childhood. Further research is needed to inform recommendations for the use of NNSs in this sensitive population.
科研通智能强力驱动
Strongly Powered by AbleSci AI