Tianshu Han

Prenatal exposure to famine and the development of hyperglycemia and type 2 diabetes in adulthood across consecutive generations: a population-based cohort study of families in Suihua, China

BACKGROUND There has been increased recognition that prenatal or perinatal nutrition has an effect on the development of type 2 diabetes (T2D) in adulthood, although studies that have directly examined whether the effect could be transmitted to the next generation remain sparse. OBJECTIVE We investigated the role of prenatal exposure to the Chinese famine in affecting future T2D risk in adulthood in 2 consecutive generations. DESIGN A total of 1034 families, including 2068 parents [parental generation (F1)] and 1183 offspring [offspring generation (F2)], were recruited from the Suihua rural area that was affected by the Chinese Famine of 1959-1961. Participants born between 1 October 1959 and 30 September 1961 were defined as famine exposed, and those born between 1 October 1962 and 30 September 1964 were defined as nonexposed. The F2 were classified as having 1) no parent exposed to famine, 2) only a mother exposed to famine, 3) only a father exposed to famine, or 4) both parents exposed to famine. Classical risk factors for T2D as well as fasting-glucose- and oral-glucose-tolerance tests were measured in both the F1 and F2. RESULTS Prenatal exposure to famine was associated with elevated risks of hyperglycemia (multivariable-adjusted OR: 1.93; 95% CI: 1.51, 2.48) and T2D (OR: 1.75; 95% CI: 1.20, 2.54) in adulthood in F1. Furthermore, compared with the offspring of nonexposed parents, the F2 with exposed parents- especially both exposed parents-had increased hyperglycemia risk (OR: 2.02; 95% CI: 1.12, 3.66) in adulthood. CONCLUSION Prenatal exposure to famine remarkably increases hyperglycemia risk in 2 consecutive generations of Chinese adults independent of known T2D risk factors, which supports the notion that prenatal nutrition plays an important role in the development of T2D across consecutive generations of Chinese adults. This trial was registered at www.chictr.org.cn as ChiCTR-ECH-13003644.

U-shaped relationships between sleep duration and metabolic syndrome and metabolic syndrome components in males: a prospective cohort study

OBJECTIVE Based on cross-sectional studies, sleep duration has been shown to have a relationship with the prevalence of metabolic syndrome (MS); however, no prospective studies have verified a correlation between the incidence of MS and the gender difference. Herein we prospectively determined the association between MS and gender using a large sample. METHODS A total of 4774 subjects without MS, 30-65 years of age, participated in this study. One-way ANOVA and Chi-square test were used to analyze the baseline variables. Cox regression models were performed separately in a mixed-gender population, males and females, while controlling for lifestyle and sleep-related factors. RESULTS During an average of 4.4-year follow-up, 1506 subjects developed MS. Both short (<6 h) and long sleep durations (8-9 and ≥9 h) increased the incidence of MS and elevated the fasting blood glucose (FBG) level in the mixed-gender population (MS: HR = 1.43, 1.25, and 1.45, respectively; elevated FBG: HR = 1.61, 1.65, and 1.98, respectively) and males (MS: HR = 1.87, 1.73, and 1.96, respectively; elevated FBG: HR = 2.27, 2.28, and 3.16, respectively). The HR(8-9 and ≥9 h) for hypertriglyceridemia in males was 1.48 and 19.4, and the HR(<6, 6-7, and ≥9 h) for hypertension in females was 1.25, 1.46, and 1.72, respectively. CONCLUSION Both short and long sleep durations were associated with a greater incidence of MS and elevated FBG in a mixed-gender population and in males, and hypertension in females. Males who sleep longer were also at a higher risk for hypertriglyceridemia.

A Snack Dietary Pattern Increases the Risk of Hypercholesterolemia in Northern Chinese Adults: A Prospective Cohort Study

The evidence about the effect of dietary patterns on blood cholesterol from cohort studies was very scarce. The study was to identify the association of dietary patterns with lipid profile, especially cholesterol, in a cohort in north China. Using a 1-year food frequency questionnaire, we assessed the dietary intake of 4515 adults from the Harbin People’s Health Study in 2008, aged 20-74 years. Principle component analysis was used to identify dietary patterns. The follow-up was completed in 2012. Fasting blood samples were collected for the determination of blood lipid concentrations. Logistic regression models were used to evaluate the association of dietary patterns with the incidence of hypercholesterolemia, hypertriglyceridemia, and low-HDL cholesterolemia. Five dietary patterns were identified (“staple food”, “vegetable, fruit and milk”, “potato, soybean and egg”, “snack”, and “meat”). The relative risk (RR) between the extreme tertiles of the snack dietary pattern scores was 1.72 (95% CI = 1.14, 2.59, P = 0.004) for hypercholesterolemia, 1.39 (1.13, 1.75, P = 0.036) for hypertriglyceridemia, after adjustment for age, sex, education, body mass index, smoking, alcohol consumption, energy intake, exercise and baseline lipid concentrations. There was a significant positive association between the snack dietary pattern scores and fasting serum total cholesterol (SRC (standardized regression coefficient) = 0.262, P = 0.025), LDL-c (SRC = 0.324, P = 0.002) and triglycerides (SRC = 0.253, P = 0.035), after adjustment for the multiple variables above. Moreover, the adjusted RR of hypertriglyceridemia between the extreme tertiles was 0.73 (0.56, 0.94, P = 0.025) for the vegetable, fruit and milk dietary pattern, and 1.86 (1.33, 2.41, P = 0.005) for the meat dietary pattern. The snack dietary pattern was a newly emerged dietary pattern in northern Chinese adults. It appears conceivable that the risk of hypercholesterolemia can be reduced by changing the snack dietary pattern.

The Harbin Cohort Study on Diet, Nutrition and Chronic Non-communicable Diseases: study design and baseline characteristics.

Diet and nutrition have been reported to be associated with many common chronic diseases and blood-based assessment would be vital to investigate the association and mechanism, however, blood-based prospective studies are limited. The Harbin Cohort Study on Diet, Nutrition and Chronic Non-communicable Diseases was set up in 2010. From 2010 to 2012, 9,734 participants completed the baseline survey, including demographic characteristics, dietary intake, lifestyles and physical condition, and anthropometrics. A re-survey on 490 randomly selected participants was done by using the same methods which were employed in the baseline survey. For all participants, the mean age was 50 years and 36% of them were men. Approximately 99.4 % of cohort members donated blood samples. The mean total energy intake was 2671.7 kcal/day in men and 2245.9 kcal/day in women, the mean body mass index was 25.7 kg/m2 in men and 24.6 kg/m2 in women, with 18.4% being obese (≥28 kg/m2), 12.7% being diabetic, and 29.5% being hypertensive. A good agreement was obtained for the physical measurements between the baseline survey and re-survey. The resources from the cohort and its fasting and postprandial blood samples collected both at baseline and in each follow-up will be valuable and powerful in investigating relationship between diet, nutrition and chronic diseases and discovering novel blood biomarkers and the metabolism of these biomarkers related to chronic diseases.

Dietary Protein Consumption and the Risk of Type 2 Diabetes: A Systematic Review and Meta-Analysis of Cohort Studies

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.

Temporal Relationship Between Hyperuricemia and Insulin Resistance and Its Impact on Future Risk of Hypertension

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 (&bgr;1 values) from baseline uric acid to follow-up insulin resistance indices were significantly greater than path coefficients (&bgr;2 values) from baseline insulin resistance indices to follow-up uric acid (&bgr;1=0.110 versus &bgr;2=0.017; P<0.001, for hepatic insulin resistance; &bgr;1=−0.208 versus &bgr;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 &bgr;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.

Low-Carbohydrate, High-Protein, High-Fat Diets Rich in Livestock, Poultry and Their Products Predict Impending Risk of Type 2 Diabetes in Chinese Individuals that Exceed Their Calculated Caloric Requirement

The evidence on the association between long-term low-carbohydrate, high-fat and high-protein diets and type 2 diabetes (T2D) is controversial. Until now, data is limited for Chinese populations, especially in considering the influence of extra energy intake. In this paper, we aimed to investigate the association of low-carbohydrate, high-fat and high-protein diets with type 2 diabetes (T2D) risk in populations consuming extra calories and those with normal caloric intake, We also determined whether the association is mediated by insulin resistance (IR) or β-cell dysfunction. A total of 3644 subjects in the Harbin People’s Health Study (Cohort 1, 2008–2012) and 7111 subjects in the Harbin Cohort Study on Diet, Nutrition and Chronic Non-Communicable Diseases (Cohort 2, 2010–2015) were analyzed, with a median follow-up of 4.2 and 5.3 years, respectively. Multivariate relative risks (RRs) and their 95% confidence intervals (95% CIs) were calculated to estimate the association between low-carbohydrate, high-fat and high-protein diet and T2D in logistic regression models. The multivariate RRs (95% CIs) were 1.00, 2.24 (1.07, 4.72) and 2.29 (1.07, 4.88) (Ptrend = 0.04), and 1.00, 1.45 (0.91, 2.31) and 1.64 (1.03, 2.61) (Ptrend = 0.04) across tertiles of low-carbohydrate, high-fat and high-protein diet scores in the population consuming extra calories in Cohort 1 and Cohort 2, respectively. The association was no longer significant after adjustment for livestock and its products, or poultry and its products. The mediation analysis discovered that this association in the population consuming extra calories was insulin resistance mediated, in both Cohort 1 and Cohort 2. However, the association was not significant among participants overall and participants with normal caloric intake. Our results indicated that long-term low-carbohydrate, high-fat and high-protein diets were associated with increased T2D risk among the population consuming extra calories, which may be caused by higher intake of animal-origin fat and protein as well as lower intake of vegetables, fruit and fiber. Additionally, the association was mediated by IR. In the population consuming extra calories, reducing the intake of livestock, poultry and their products and increasing the intake of vegetables, fruit and fiber might protect this population from developing T2D.

Dietary Information Improves Model Performance and Predictive Ability of a Noninvasive Type 2 Diabetes Risk Model

There is no diabetes risk model that includes dietary predictors in Asia. We sought to develop a diet-containing noninvasive diabetes risk model in Northern China and to evaluate whether dietary predictors can improve model performance and predictive ability. Cross-sectional data for 9,734 adults aged 20–74 years old were used as the derivation data, and results obtained for a cohort of 4,515 adults with 4.2 years of follow-up were used as the validation data. We used a logistic regression model to develop a diet-containing noninvasive risk model. Akaike’s information criterion (AIC), area under curve (AUC), integrated discrimination improvements (IDI), net classification improvement (NRI) and calibration statistics were calculated to explicitly assess the effect of dietary predictors on a diabetes risk model. A diet-containing type 2 diabetes risk model was developed. The significant dietary predictors including the consumption of staple foods, livestock, eggs, potato, dairy products, fresh fruit and vegetables were included in the risk model. Dietary predictors improved the noninvasive diabetes risk model with a significant increase in the AUC (delta AUC = 0.03, P<0.001), an increase in relative IDI (24.6%, P-value for IDI <0.001), an increase in NRI (category-free NRI = 0.155, P<0.001), an increase in sensitivity of the model with 7.3% and a decrease in AIC (delta AIC = 199.5). The results of the validation data were similar to the derivation data. The calibration of the diet-containing diabetes risk model was better than that of the risk model without dietary predictors in the validation data. Dietary information improves model performance and predictive ability of noninvasive type 2 diabetes risk model based on classic risk factors. Dietary information may be useful for developing a noninvasive diabetes risk model.

Dietary Flavonoids, Copper Intake, and Risk of Metabolic Syndrome in Chinese Adults

The effects of flavonoids and copper (Cu) on metabolic syndrome (MetS) have been investigated separately, but no information exists about the joint associations between flavonoids and Cu on the risk of MetS in population studies. In this cross-sectional study, a total of 9108 people aged 20–75 years from the Harbin Cohort Study on Diet, Nutrition, and Chronic Non-Communicable Diseases (HDNNCDS) were included. Flavonoid intakes were calculated based on the flavonoid database created in our laboratory. Cu and other nutrient intakes were estimated using the Chinese Food Composition Table. Among all study subjects, a total of 2635 subjects (28.9%) met the diagnostic criteria for inclusion in the MetS group. Total flavonoids (fourth vs. first quartile, odds ratio (OR): 0.77, 95% confidence interval (CI) 0.66–0.90, Ptrend = 0.002) and Cu (OR 0.81, 90% CI: 0.70–0.94, Ptrend = 0.020) were inversely associated with the risk of MetS after adjusting for potential confounders. Higher flavonoid intake was more strongly associated with a lower risk of MetS with high levels of Cu intake (Pinteraction = 0.008). Dose–response effects showed an L-shaped curve between the total intake of five flavonoids and the risk of MetS. These results suggest that higher flavonoid intake is associated with a lower risk of MetS, especially under high levels of Cu intake.

Temporal relationship between hyperuricemia and obesity, and its association with future risk of type 2 diabetes

Background/objectives:Although hyperuricemia and obesity are significantly correlated, their temporal relationship and whether this relationship is associated with future risk of diabetes are largely unknown. This study examined temporal relationship between hyperuricemia and obesity, and its association with future risk of type 2 diabetes.Subjects/methods:This study examined two longitudinal cohorts totally including 17,044 subjects from China with an average of 6.0 years follow-up. Measurements of body mass index (BMI), waist circumference (WC), percentage of body fat and fasting serum uric acid were obtained at two time points. Cross-lagged panel and mediation analysis were used to examine the temporal relationship between hyperuricemia and obesity, and the association of this temporal relationship with follow-up diabetes.Results:In combined data of the two cohorts, the cross-lagged path coefficient (β1 = 0.121; 95% confidence interval (CI): 0.108–0.135) from baseline uric acid to the follow-up BMI was significantly greater than the path coefficient (β2 = 0.055, 95% CI: 0.038–0.072) from baseline BMI to the follow-up uric acid (P = 8.14e−10 for the difference between β1 and β2) with adjustment for covariates. The separate cross-lagged path models of uric acid with WC and percentage of body fat showed temporal patterns similar to that noted for uric acid with BMI. Further, the path coefficient (β1) from baseline uric acid to follow-up BMI in the group with diabetes was significantly greater than without diabetes (P = 0.003 for the difference of β1s in the two groups). BMI partially mediated the association of uric acid with risk of diabetes, and the percentage of mediated-association was estimated at 20.3% (95% CI: 15.7–24.8%). Results of these analyses in the combined data were consistent with those in the two cohorts, respectively.Conclusions:These findings indicated that increased uric acid levels probably associated with obesity and type 2 diabetes, and more definite research is needed to define any role for uric acid in relation to these diseases.