Tolerable upper intake level for dietary sugars

Abstract

Following a request from five European Nordic countries, the EFSA Panel on Nutrition, Novel Foods and Food Allergens (NDA) was tasked to provide scientific advice on a tolerable upper intake level (UL) or a safe level of intake for dietary (total/added/free) sugars based on available data on chronic metabolic diseases, pregnancy-related endpoints and dental caries. Specific sugar types (fructose) and sources of sugars were also addressed. The intake of dietary sugars is a well-established hazard in relation to dental caries in humans. Based on a systematic review of the literature, prospective cohort studies do not support a positive relationship between the intake of dietary sugars, in isocaloric exchange with other macronutrients, and any of the chronic metabolic diseases or pregnancy-related endpoints assessed. Based on randomised control trials on surrogate disease endpoints, there is evidence for a positive and causal relationship between the intake of added/free sugars and risk of some chronic metabolic diseases: The level of certainty is moderate for obesity and dyslipidaemia (> 50-75% probability), low for non-alcoholic fatty liver disease and type 2 diabetes (> 15-50% probability) and very low for hypertension (0-15% probability). Health effects of added vs. free sugars could not be compared. A level of sugars intake at which the risk of dental caries/chronic metabolic diseases is not increased could not be identified over the range of observed intakes, and thus, a UL or a safe level of intake could not be set. Based on available data and related uncertainties, the intake of added and free sugars should be as low as possible in the context of a nutritionally adequate diet. Decreasing the intake of added and free sugars would decrease the intake of total sugars to a similar extent. This opinion can assist EU Member States in setting national goals/recommendations.

Keywords: Tolerable upper intake level; added sugars; chronic metabolic diseases; dental caries; free sugars; pregnancy‐related endpoints; safe level of intake.

Figure 1

Stepwise process to provide scientific advice on total/added/free sugars

Figure 2

Classification of dietary sugars

Figure 3

Methodology used to estimate intakes of total, free and added sugars in European countries

Figure 4

Adaptation of the definitions of added and free sugars for the development of the food composition database

Figure 5

Conceptual framework for the systematic reviews on sugars intake in relation to disease endpoints and other endpoints

Figure 6

Answer format for the risk of bias (RoB) questions^(a) (a): Source: OHAT/NTP RoB tool

Figure 7

Exposure–disease relationships investigated for hazard identification Each arrow represents one specific subquestion. Five types of exposure and seven metabolic diseases have been identified based on the evidence availability resulting from the study selection process. sQx = subquestion by exposure.

Figure 8

Graphical representation of standalone and complementary lines of evidence with some examples

Figure 9

Stepwise approach for evidence integration and uncertainty analysis applied to each subquestion by study design ¹: For subquestions with more than one standalone LoE, and for standalone LoEs with endpoints which are biologically related, the comprehensive uncertainty analysis is undertaken for the endpoint with the highest level of evidence for a positive relationship with the exposure. The endpoint will be selected by expert judgement i.e. considering the number of studies available, and the strength, consistency and biological plausibility of the relationship. ²: Complementary LoEs are assessed and discussed considering the factors underpinning the preliminary UA to provide a complete picture of the evidence base available for the sQ and inform the identification of data gaps. Yet, in the absence of evidence from Standalone LoE, evidence from complementary LoEs cannot be used to conclude on a positive and causal relationship between the exposure and the risk of disease.

Figure 10

Approach applied to assign the final level of certainty in a causal relationship^{(a) (a)}: Adapted from OHAT (NTP, 2019).

Figure 11

Approach for evidence integration and uncertainty analysis across study designs applied to each subquestion

Figure 12

Meta‐regressive dose‐response linear model between the intake of added and free sugars (E%) and fasting glucose Blue = RoB Tier 1; Red = RoB Tier 2.

Figure 13

Dose‐response meta‐analysis on the relationship between the intake of sugar‐sweetened beverages and incidence of type 2 diabetes mellitus (T2DM)

Figure 14

Dose‐response meta‐analysis on the relationship between the intake of fruit juices and incidence of Type 2 diabetes mellitus (T2DM)

Figure 15

Meta‐regressive dose‐response linear model between the intake of added and free sugars (E%) and fasting triglycerides

Figure 16

Dose‐response meta‐analysis on the relationship between the intake of sugar‐sweetened beverages and incidence of hypertension (HTN)

Figure 17

Dose‐response meta‐analysis on the relationship between the intake of sugar‐sweetened beverages and risk of cardiovascular disease (CVD) – composite endpoint

Figure 18

Distribution of randomised controlled trials addressing different endpoints by ranges of added or free sugars intake, corresponding to between‐arm differences in intake Legend to Figure  18 . Since each randomised controlled trial (RCT) can investigate more than one endpoint, the total number of studies in the figure is higher than the number of RCTs included in the assessment.

Figure C.1: Flow chart for the selection of studies on metabolic diseases *: Articles identified through the update of the literature search that were incorporated into the assessment (see Annex A).

Figure C.2: Flow chart for the selection of studies on caries

Figure H.1: RCTs on the effect of high vs. low sugar intake ad libitum on body weight

Figure H.2: RCTs on the effect of high vs. low sugar intake on liver fat

Figure H.3: RCTs on the effect of high vs. low sugar intake on fasting glucose

Figure H.4: Funnel plot. RCTs on the effect of high vs. low sugar intake on fasting triglycerides

Figure H.5: Funnel plot. RCTs on the effect of high vs. low sugar intake on systolic blood pressure

Figure I.1: Summary of Risk of Bias ratings for RCTs on the effect of high vs. low sugar intake on body weight

Figure I2

Summary of Risk of Bias ratings for RCTs on the effect of high vs. low sugar intake on liver fat

Figure I3

Summary of Risk of Bias ratings for RCTs on the effect of high vs low sugar intake on fasting glucose

Figure I4

Summary of Risk of Bias ratings for RCTs on the effect of high vs. low sugar intake on fasting triglycerides

Figure I5

Summary of Risk of Bias ratings for RCTs on the effect of high vs. low sugar intake on systolic blood pressure

Figure I6

Summary of Risk of Bias ratings for RCTs on effect of fructose vs. glucose on uric acid