Gestational diabetes mellitus (GDM) is a common medical complication in pregnancy, carries adverse health outcomes for both mothers and offspring. However, national data on the prevalence and secular trends of GDM during the past 10 years in the U.S. is lacking. This study included 26,340 ever-pregnant women aged ≥ 18 years from the National Health Interview Survey in 20and 2016. We examined GDM prevalence in 20and 2016. The prevalence of GDM increased from 4.6% in 20to 8.2% in 2016 (P<0.001). non-Hispanic white women showed less increase in the prevalence (2.8%) than non-Hispanic black women (3.8%), Hispanic women (4.1%), and women with other race/ethnicity (8.4%). The prevalence of GDM in non-Hispanic white women was higher than in non-Hispanic black (P=0.01) and women with other race/ethnicity (P=0.01) in 2006; but similar with in non-Hispanic black and lower than in women with other race/ethnicity (p=0.02) in 2016. The prevalence of GDM in non-Hispanic white and Hispanic women was similar in 20and 2016. In addition, the increase of GDM was more evident among women who were overweight, had low income, aged between 45-64 years, and had insufficient physical activity. In conclusion, the prevalence of GDM increased by 3.6% from 20to 2016; and the rise was more marked among non-white, overweight, low income, age 45-64 years, and insufficient activity groups. Disclosure T. Zhou: None. D. Sun: None. X. Li: None. Y. Heianza: None. H. Nisa: None. G. Hu: None. X. Pei: None. X. Shang: None. L. Qi: None.

BACKGROUND Associations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined. METHODS We performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies. RESULTS Higher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00–0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14–0.25) serving/day higher dairy intake (P = 3.15×10−12) and 0.12 (95% CI, 0.06–0.17) kg/m2 higher BMI (P = 2.11×10−5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27–0.92; P = 3.0×10−4). CONCLUSIONS The present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.

Background There is an evidence gap about whether a low-risk lifestyle is as important as achieving blood pressure (BP) and random blood glucose (RBG) control. Objectives To explore the long-term impacts and relative importance of low-risk lifestyle and health factors on the risk of all-cause and cancer mortality and macrovascular and microvascular complications among diabetic patients. Methods This study included 26,004 diabetes patients in the China Kadoorie Biobank. We defined five lifestyle factors (smoking, alcohol drinking, physical activity, fruits and vegetables intake, and waist-to-hip ratio) and two health factors (BP and RBG). Cox regression was used to yield adjusted hazard ratios (HRs) and confidence intervals (CIs) for individual and combined lifestyle and health factors with the risks of diabetes-related outcomes. Results There were 5,063 deaths, 6,848 macrovascular complications, and 2,055 microvascular complications that occurred during a median follow-up of 10.2 years. Combined low-risk lifestyle factors were associated with lower risk of all main outcomes, with HRs (95%CIs) for participants having 4-5 low-risk factors versus 0-1 of 0.50 (0.44 to 0.57) for all-cause mortality, 0.55 (0.43 to 0.71) for cancer mortality, 0.60 (0.54 to 0.67) for macrovascular complications, and 0.75 (0.62 to 0.91) for microvascular complications. The combined 4-5 low-risk lifestyle factors showed relative importance in predicting all-cause and cancer mortality and macrovascular complications. Conclusions Assuming causality exists, our findings suggest that adopting a low-risk lifestyle should be regarded as important as achieving ideal BP and glycemic goals in the prevention and management of diabetes-related adverse outcomes.

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