Objective: Because of blood lipid concerns, diabetes associations discourage fructose at high intakes. To quantify the effect of fructose on blood lipids in diabetes, we conducted a systematic review and meta-analysis of experimental clinical trials investigating the effect of isocaloric fructose exchange for carbohydrate on triglycerides, total cholesterol, LDL cholesterol, and HDL cholesterol in type 1 and 2 diabetes.
Research design and methods: We searched MEDLINE, EMBASE, CINAHL, and the Cochrane Library for relevant trials of > or =7 days. Data were pooled by the generic inverse variance method and expressed as standardized mean differences with 95% CI. Heterogeneity was assessed by chi(2) tests and quantified by I(2). Meta-regression models identified dose threshold and independent predictors of effects.
Results: Sixteen trials (236 subjects) met the eligibility criteria. Isocaloric fructose exchange for carbohydrate raised triglycerides and lowered total cholesterol under specific conditions without affecting LDL cholesterol or HDL cholesterol. A triglyceride-raising effect without heterogeneity was seen only in type 2 diabetes when the reference carbohydrate was starch (mean difference 0.24 [95% CI 0.05-0.44]), dose was >60 g/day (0.18 [0.00-0.37]), or follow-up was < or =4 weeks (0.18 [0.00-0.35]). Piecewise meta-regression confirmed a dose threshold of 60 g/day (R(2) = 0.13)/10% energy (R(2) = 0.36). A total cholesterol-lowering effect without heterogeneity was seen only in type 2 diabetes under the following conditions: no randomization and poor study quality (-0.19 [-0.34 to -0.05]), dietary fat >30% energy (-0.33 [-0.52 to -0.15]), or crystalline fructose (-0.28 [-0.47 to -0.09]). Multivariate meta-regression analyses were largely in agreement.
Conclusions: Pooled analyses demonstrated conditional triglyceride-raising and total cholesterol-lowering effects of isocaloric fructose exchange for carbohydrate in type 2 diabetes. Recommendations and large-scale future trials need to address the heterogeneity in the data.