The prevalence of diabetes is increasing rapidly in China. However, evidence is limited about its effects on chronic liver diseases and liver cancer. We examined the associations of diabetes with chronic liver diseases and liver cancer and of random plasma glucose (RPG) with these liver diseases among participants without diabetes in Chinese adults and the possible interaction by hepatitis B virus (HBV) infection. The prospective China Kadoorie Biobank recruited 512,891 adults. During 10 years of follow‐up, 2,568 liver cancer, 2,082 cirrhosis, 1,298 hospitalized nonalcoholic fatty liver disease (NAFLD), and 244 hospitalized alcoholic liver disease (ALD) cases were recorded among 503,993 participants without prior history of cancer or chronic liver diseases at baseline. Cox regression was used to estimate hazard ratios (HRs) for each disease by diabetes status (previously diagnosed or screen‐detected) and, among those without previously diagnosed diabetes, by levels of RPG. Overall 5.8% of participants had diabetes at baseline. Compared to those without diabetes, individuals with diabetes had adjusted HRs of 1.49 (95% confidence interval 1.30‐1.70) for liver cancer, 1.81 (1.57‐2.09) for cirrhosis, 1.76 (1.47‐2.16) for NAFLD, and 2.24 (1.42‐3.54) for ALD. The excess risks decreased but remained elevated in those with longer duration. Among those without previously diagnosed diabetes, RPG was positively associated with liver diseases, with adjusted HRs per 1 mmol/L higher RPG of 1.04 (1.03‐1.06) for liver cancer, 1.07 (1.05‐1.09) for cirrhosis, 1.07 (1.05‐1.10) for NAFLD, and 1.10 (1.05‐1.15) for ALD. These associations did not differ by HBV infection. Conclusion: In Chinese adults, diabetes and higher blood glucose levels among those without known diabetes are associated with higher risks of liver cancer and major chronic liver diseases.

Aims  The potential difference in the impacts of lifestyle factors (LFs) on progression from healthy to first cardiometabolic disease (FCMD), subsequently to cardiometabolic multimorbidity (CMM), and further to death is unclear. Methods and results  We used data from the China Kadoorie Biobank of 461 047 adults aged 30–79 free of heart disease, stroke, and diabetes at baseline. Cardiometabolic multimorbidity was defined as the coexistence of two or three CMDs, including ischaemic heart disease (IHD), stroke, and type 2 diabetes (T2D). We used multi-state model to analyse the impacts of high-risk LFs (current smoking or quitting because of illness, current excessive alcohol drinking or quitting, poor diet, physical inactivity, and unhealthy body shape) on the progression of CMD. During a median follow-up of 11.2 years, 87 687 participants developed at least one CMD, 14 164 developed CMM, and 17 541 died afterwards. Five high-risk LFs played crucial but different roles in all transitions from healthy to FCMD, to CMM, and then to death. The hazard ratios (95% confidence intervals) per one-factor increase were 1.20 (1.19, 1.21) and 1.14 (1.11, 1.16) for transitions from healthy to FCMD, and from FCMD to CMM, and 1.21 (1.19, 1.23), 1.12 (1.10, 1.15), and 1.10 (1.06, 1.15) for mortality risk from healthy, FCMD, and CMM, respectively. When we further divided FCMDs into IHD, ischaemic stroke, haemorrhagic stroke, and T2D, we found that LFs played different roles in disease-specific transitions even within the same transition stage. Conclusion  Assuming causality exists, our findings emphasize the significance of integrating comprehensive lifestyle interventions into both health management and CMD management.

Diabetes is associated with an increased risk of pancreatic cancer (PC) in Western populations. Uncertainty remains, however, about the relevance of plasma glucose for PC among people without diabetes and about the associations of diabetes and high blood glucose with PC in China where the increase in diabetes prevalence has been very recent. The prospective China Kadoorie Biobank (CKB) study recruited 512,000 adults aged 30‐79 years from 10 diverse areas of China during 2004‐2008, recording 595 PC cases during 8 years of follow‐up. Cox regression yielded adjusted hazard ratios (HRs) for PC associated with diabetes (previously diagnosed or screen‐detected) and, among those without previously diagnosed diabetes, with levels of random plasma glucose (RPG). These were further meta‐analysed with 22 published prospective studies. Overall 5.8% of CKB participants had diabetes at baseline. Diabetes was associated with almost twofold increased risk of PC (adjusted HR = 1.87, 95% CI 1.48‐2.37), with excess risk higher in those with longer duration since diagnosis (p for trend = 0.01). Among those without previously diagnosed diabetes, each 1 mmol/L higher usual RPG was associated with a HR of 1.12 (1.04‐1.21). In meta‐analysis of CKB and 22 other studies, previously diagnosed diabetes was associated with a 52% excess risk (1.52, 1.43‐1.63). Among those without diabetes, each 1 mmol/L higher blood glucose was associated with a 15% (1.15, 1.09‐1.21) excess risk. In Chinese and non‐Chinese populations, diabetes and higher blood glucose levels among those without diabetes are associated with an increased risk of PC.

BackgroundLittle prospective evidence exists about risk factors and prognosis of acute pancreatitis in China. We examined the associations of certain metabolic and lifestyle factors with risk of acute pancreatitis in Chinese adults.Methods and findingsThe prospective China Kadoorie Biobank (CKB) recruited 512,891 adults aged 30 to 79 years from 5 urban and 5 rural areas between 25 June 2004 and 15 July 2008. During 9.2 years of follow-up (to 1 January 2015), 1,079 cases of acute pancreatitis were recorded. Cox regression was used to estimate adjusted hazard ratios (HRs) for acute pancreatitis associated with various metabolic and lifestyle factors among all or male (for smoking and alcohol drinking) participants. Overall, the mean waist circumference (WC) was 82.1 cm (SD 9.8) cm in men and 79.0 cm (SD 9.5) cm in women, 6% had diabetes, and 6% had gallbladder disease at baseline. WC was positively associated with risk of acute pancreatitis, with an adjusted HR of 1.35 (95% CI 1.27–1.43; p < 0.001) per 1-SD-higher WC. Individuals with diabetes or gallbladder disease had HRs of 1.34 (1.07–1.69; p = 0.01) and 2.42 (2.03–2.88; p < 0.001), respectively. Physical activity was inversely associated with risk of acute pancreatitis, with each 4 metabolic equivalent of task (MET) hours per day (MET-h/day) higher physical activity associated with an adjusted HR of 0.95 (0.91–0.99; p = 0.03). Compared with those without any metabolic risk factors (i.e., obesity, diabetes, gallbladder disease, and physical inactivity), the HRs of acute pancreatitis for those with 1, 2, or ≥3 risk factors were 1.61 (1.47–1.76), 2.36 (2.01–2.78), and 3.41 (2.46–4.72), respectively (p < 0.001). Among men, heavy alcohol drinkers (≥420 g/week) had an HR of 1.52 (1.11–2.09; p = 0.04, compared with abstainers), and current regular smokers had an HR of 1.45 (1.28–1.64; p = 0.02, compared with never smokers). Following a diagnosis of acute pancreatitis, there were higher risks of pancreatic cancer (HR = 8.26 [3.42–19.98]; p < 0.001; 13 pancreatic cancer cases) and death (1.53 [1.17–2.01]; p = 0.002; 89 deaths). Other diseases of the pancreas had similar risk factor profiles and prognosis to acute pancreatitis. The main study limitations are ascertainment of pancreatitis using hospital records and residual confounding.ConclusionsIn this relatively lean Chinese population, several modifiable metabolic and lifestyle factors were associated with higher risks of acute pancreatitis, and individuals with acute pancreatitis had higher risks of pancreatic cancer and death.

High-sensitivity cTnT and NT-proBNP were independently associated with incident PAD, particularly its severe form, CLI. Although future studies are warranted to investigate pathophysiological mechanisms behind these associations, our study suggests the usefulness of cardiac markers to identify individuals at high risk of CLI.

Background Natural and anthropogenic sources of metal exposure differ for urban and rural residents. We searched to identify patterns of metal mixtures which could suggest common environmental sources and/or metabolic pathways of different urinary metals, and compared metal-mixtures in two population-based studies from urban/sub-urban and rural/town areas in the US: the Multi-Ethnic Study of Atherosclerosis (MESA) and the Strong Heart Study (SHS). Methods We studied a random sample of 308 White, Black, Chinese-American, and Hispanic participants in MESA (2000–2002) and 277 American Indian participants in SHS (1998–2003). We used principal component analysis (PCA), cluster analysis (CA), and linear discriminant analysis (LDA) to evaluate nine urinary metals (antimony [Sb], arsenic [As], cadmium [Cd], lead [Pb], molybdenum [Mo], selenium [Se], tungsten [W], uranium [U] and zinc [Zn]). For arsenic, we used the sum of inorganic and methylated species (∑As). Results All nine urinary metals were higher in SHS compared to MESA participants. PCA and CA revealed the same patterns in SHS, suggesting 4 distinct principal components (PC) or clusters (∑As-U-W, Pb-Sb, Cd-Zn, Mo-Se). In MESA, CA showed 2 large clusters (∑As-Mo-Sb-U-W, Cd-Pb-Se-Zn), while PCA showed 4 PCs (Sb-U-W, Pb-Se-Zn, Cd-Mo, ∑As). LDA indicated that ∑As, U, W, and Zn were the most discriminant variables distinguishing MESA and SHS participants. Conclusions In SHS, the ∑As-U-W cluster and PC might reflect groundwater contamination in rural areas, and the Cd-Zn cluster and PC could reflect common sources from meat products or metabolic interactions. Among the metals assayed, ∑As, U, W and Zn differed the most between MESA and SHS, possibly reflecting disproportionate exposure from drinking water and perhaps food in rural Native communities compared to urban communities around the US.

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Liming Li and colleagues highlight the importance of identifying people without symptoms to control outbreaks of covid-19Box 1: Definitions of asymptomatic and pre-symptomatic Asymptomatic infectionAn asymptomatic case is one in which someone has laboratory confirmed SARS-CoV-2 infection but does not develop symptoms (ie, fever, dry cough, fatigue). Asymptomatic transmission refers to transmission of the virus from a person who did not develop disease symptoms. Pre-symptomatic infectionPre-symptomatic cases are those in which infection is detected before the person develops symptoms. Pre-symptomatic transmission is defined as transmission that occurs during the pre-symptomatic phase of the viral incubation period. 3 4