Recently, some studies have focused on the relationship between dietary protein intake and the risk of type 2 diabetes mellitus (T2DM), but the conclusions have been inconsistent. Therefore, in this paper, a systematic review and meta-analysis of cohort studies regarding protein consumption and T2DM risk are conducted in order to present the association between them. We searched the PubMed and Embase databases for cohort studies on dietary protein, high-protein food consumption and risk of T2DM, up to July 2017. A summary of relative risks was compiled by the fixed-effect model or random-effect model. Eleven cohort studies regarded protein intake and T2DM (52,637 cases among 483,174 participants). The summary RR and 95% CI (Confidence Interval) of T2DM was 1.12 (1.08–1.17) in all subjects, 1.13 (1.04–1.24) in men, and 1.09 (1.04–1.15) in women for total protein;1.14 (1.09–1.19) in all subjects, 1.23 (1.09–1.38) in men, and 1.11 (1.03–1.19) in women for animal protein; 0.96 (0.88–1.06) in all subjects, 0.98 (0.72–1.34) in men, and 0.92 (0.86–0.98) in women for plant protein. We also compared the association between different food sources of protein and the risk of T2DM. The summary RR (Relative Risk) and 95% CI of T2DM was 1.22 (1.09–1.36) for red meat, 1.39 (1.29–1.49) for processed meat, 1.03 (0.89–1.17) for fish, 1.03 (0.64–1.67) for egg, 0.89 (0.84–0.94) for total dairy products, 0.87 (0.78–0.96) for whole milk, 0.83 (0.70–0.98) for yogurt, 0.74 (0.59–0.93) in women for soy. This meta-analysis shows that total protein and animal protein could increase the risk of T2DM in both males and females, and plant protein decreases the risk of T2DM in females. The association between high-protein food types and T2DM are also different. Red meat and processed meat are risk factors of T2DM, and soy, dairy and dairy products are the protective factors of T2DM. Egg and fish intake are not associated with a decreased risk of T2DM. This research indicates the type of dietary protein and food sources of protein that should be considered for the prevention of diabetes.

Although hyperuricemia and insulin resistance significantly correlated, their temporal sequence and how the sequence influence on future risk of hypertension are largely unknown. This study assessed temporal relationship between uric acid and insulin resistance and its impact on future risk of hypertension by examining a longitudinal cohort including 8543 subjects aged 20 to 74 years from China, with an average follow-up of 5.3 years. Measurements of fasting uric acid, as well as fasting and 2-hour serum glucose and insulin, were obtained at baseline and follow-up. Indicators of hepatic and peripheral insulin resistance were calculated. Cross-lagged panel and mediation analysis were used to examine the temporal relationship between uric acid and insulin resistance and its impact on follow-up hypertension. After adjusting for covariates, the cross-lagged path coefficients ( β ₁ values) from baseline uric acid to follow-up insulin resistance indices were significantly greater than path coefficients ( β ₂ values) from baseline insulin resistance indices to follow-up uric acid ( β ₁ =0.110 versus β ₂ =0.017; P <0.001, for hepatic insulin resistance; β ₁ =−0.208 versus β ₂ =−0.021; P <0.001, for peripheral insulin resistance). The path coefficients from baseline uric acid to follow-up insulin resistance indices in the hypertensive group were significantly greater than that in the normotensive group ( P <0.001 for the difference of β ₁ values in the 2 groups). Insulin resistance partially mediated the effect of uric acid on subsequent hypertension, and the mediation effect of peripheral insulin resistance was significantly greater than that of hepatic insulin resistance (31.3% versus 13.2%; P <0.001, for the difference of mediation effects). These findings provide evidence that higher uric acid levels probably precede insulin resistance, and peripheral insulin resistance likely plays a more important role in the development of hypertension than hepatic insulin resistance does.

OBJECTIVE: This randomized controlled-feeding trial aimed to determine the impact of fried meat intake on the gut microbiota and fecal cometabolites and whether such impacts influenced host glucose homoeostasis, intestinal endotoxin levels, and systemic inflammation. RESEARCH DESIGN AND METHODS: A total of 117 overweight adults were randomized into two groups. Fifty-nine participants were provided fried meat four times per week, and 58 participants were restricted from fried meat intake, while holding food group and nutrient compositions constant, for 4 weeks. The gut microbiota was analyzed by 16S rRNA sequencing. Glucose and insulin concentrations at 0, 30, 60, and 120 min of an oral glucose tolerance test, fecal microbiota-host cometabolite levels, and intestinal endotoxin and inflammation serum biomarker levels were measured. The area under the curve (AUC) for insulin, insulinogenic index (IGI), and muscle insulin resistance index (MIRI) were calculated. RESULTS: The participants who consumed fried meat had lower IGI values than the control subjects, but they had higher MIRI and AUC values of insulin and lipopolysaccharide (LPS), TNF-α, IL-10, and IL-1β levels (P < 0.05). Fried meat intake lowered microbial community richness and decreased Lachnospiraceae and Flavonifractor abundances while increasing Dialister, Dorea, and Veillonella abundances (P FDR <0.05), provoking a significant shift in the fecal cometabolite profile, with lower 3-indolepropionic acid, valeric acid, and butyric acid concentrations and higher carnitine and methylglutaric acid concentrations (P FDR <0.05). Changes in these cometabolite levels were significantly associated with changes in IGI and MIRI values and LPS, FGF21, TNF-α, IL-1β, and IL-10 levels (P < 0.05). CONCLUSIONS: Fried meat intake impaired glucose homoeostasis and increased intestinal endotoxin and systemic inflammation levels by influencing the gut microbiota and microbial-host cometabolites.