Objective: Reviews on the relationship of low-energy sweeteners (LES) with body weight (BW) have reached widely differing conclusions. To assess possible citation bias, citation analysis was used to quantify the relevant characteristics of cited articles, and explore citation patterns in relation to review conclusions.

Design: A systematic search identified reviews published from January 2010 to March 2020. Different characteristics (for example, type of review or research, journal impact factor, conclusions) were extracted from the reviews and cited articles. Logistic regression was used to estimate likelihood of articles with particular characteristics being cited in reviews. A qualitative network analysis linked reviews sub-grouped by conclusions with the types of articles they cited. 

Main outcome measures: (OR; 95% CI) for likelihood that articles with particular characteristics were cited as evidence in reviews. Results: From 33 reviews identified, 183 different articles were cited (including other reviews). Narrative reviews were 62% less likely to be cited than systematic reviews with meta-analysis (OR 0.38; 0.16 to 0.86; p=0.03). Likelihood of being cited was higher for evidence on children than adults (OR 2.27; 1.59 to 3.25; p<0.0001), and with increased journal impact factor (OR 1.15; 1.00 to 1.31; p=0.04). No other factors were statistically significant in the main analysis, and few factors were significant in subgroup analyses. Network analysis showed that reviews concluding a beneficial relationship of LES with BW cited mainly randomised controlled trials, whereas reviews concluding an adverse relationship cited mainly observational studies. 

Conclusions: Overall reference to the available evidence across reviews appears largely arbitrary, making citation bias likely. Differences in the conclusions of individual reviews map onto different types of evidence cited. Overall, inconsistent and selective use of the available evidence may account for the diversity of conclusions in reviews on LES and BW. 

Trial registration number: Prior to data analysis, the protocol was registered with the Open Science Framework (https://osf.io/9ghws).