Association between sugar-sweetened and artificially sweetened soft drinks and type 2 diabetes: systematic review and dose–response meta-analysis of prospective studies

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

The intake of sugar-sweetened soft drinks has been reported to be associated with an increased risk of type 2 diabetes, but it is unclear whether this is because of the sugar content or related lifestyle factors, whether similar associations hold for artificially sweetened soft drinks, and how these associations are related to BMI. We aimed to conduct a systematic literature review and dose–response meta-analysis of evidence from prospective cohorts to explore these issues. We searched multiple sources for prospective studies on sugar-sweetened and artificially sweetened soft drinks in relation to the risk of type 2 diabetes. Data were extracted from eleven publications on nine cohorts. Consumption values were converted to ml/d, permitting the exploration of linear and non-linear dose–response trends. Summary relative risks (RR) were estimated using a random-effects meta-analysis. The summary RR for sugar-sweetened and artificially sweetened soft drinks were 1·20/330 ml per d (95 % CI 1·12, 1·29, P< 0·001) and 1·13/330 ml per d (95 % CI 1·02, 1·25, P= 0·02), respectively. The association with sugar-sweetened soft drinks was slightly lower in studies adjusting for BMI, consistent with BMI being involved in the causal pathway. There was no evidence of effect modification, though both these comparisons lacked power. Overall between-study heterogeneity was high. The included studies were observational, so their results should be interpreted cautiously, but findings indicate a positive association between sugar-sweetened soft drink intake and type 2 diabetes risk, attenuated by adjustment for BMI. The trend was less consistent for artificially sweetened soft drinks. This may indicate an alternative explanation, such as lifestyle factors or reverse causality. Future research should focus on the temporal nature of the association and whether BMI modifies or mediates the association.

Related collections

Most cited references 41

Record: found
Abstract: found
Article: not found

Quantifying heterogeneity in a meta-analysis.

Julian P T Higgins, Simon G Thompson (2002)

The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.

0 comments Cited 5653 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

Meta-analysis of Observational Studies in EpidemiologyA Proposal for Reporting

Donna Stroup (2000)

0 comments Cited 1339 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Consuming fructose-sweetened, not glucose-sweetened, beverages increases visceral adiposity and lipids and decreases insulin sensitivity in overweight/obese humans.

Kimber L. Stanhope, Jean Schwarz, Nancy Keim … (2009)

Studies in animals have documented that, compared with glucose, dietary fructose induces dyslipidemia and insulin resistance. To assess the relative effects of these dietary sugars during sustained consumption in humans, overweight and obese subjects consumed glucose- or fructose-sweetened beverages providing 25% of energy requirements for 10 weeks. Although both groups exhibited similar weight gain during the intervention, visceral adipose volume was significantly increased only in subjects consuming fructose. Fasting plasma triglyceride concentrations increased by approximately 10% during 10 weeks of glucose consumption but not after fructose consumption. In contrast, hepatic de novo lipogenesis (DNL) and the 23-hour postprandial triglyceride AUC were increased specifically during fructose consumption. Similarly, markers of altered lipid metabolism and lipoprotein remodeling, including fasting apoB, LDL, small dense LDL, oxidized LDL, and postprandial concentrations of remnant-like particle-triglyceride and -cholesterol significantly increased during fructose but not glucose consumption. In addition, fasting plasma glucose and insulin levels increased and insulin sensitivity decreased in subjects consuming fructose but not in those consuming glucose. These data suggest that dietary fructose specifically increases DNL, promotes dyslipidemia, decreases insulin sensitivity, and increases visceral adiposity in overweight/obese adults.