Tibetans’ life expectancy lags behind China’s average. Obesity and noncommunicable diseases (NCDs) contribute to health disparity, but NCD patterns among Tibetans are unknown. To examine the prevalence, management, and associated factors for obesity, hypertension, and diabetes among Tibetans, compared with China’s average, we systematically searched PubMed and China National Knowledge Infrastructure databases for studies between January 2010 and April 2021. Thirty-nine studies were included for systematic review, among thirty-seven that qualified for meta-analysis, with 115,403 participants. Pooled prevalence was 47.9% (95% CI 38.0–57.8) for overweight/obesity among adults (BMI ≥ 24 kg/m²) and 15.4% (13.7–17.2) among children using Chinese criteria, which are lower than the national rates of 51.2% and 19.0%, respectively. The estimate for hypertension (31.4% [27.1–35.7]) exceeded China’s average (27.5%), while diabetes (7.5% [5.2–9.8]) was lower than average (11.9%). Men had a higher prevalence of the three conditions than women. Residents in urban areas, rural areas, and Buddhist institutes had monotonically decreased prevalence in hypertension and diabetes. Awareness, treatment, and control rates for hypertension and diabetes were lower than China’s average. Urban residence and high altitude were consistent risk factors for hypertension. Limited studies investigated factors for diabetes, yet none exist for obesity. Tibetans have high burdens of obesity and hypertension. Representative and longitudinal studies are needed for tailored interventions. There are considerable variations in study design, study sample selection, and data-analysis methods, as well as estimates of reviewed studies.

The WHO Western Pacific region bears disproportionate deaths from non-communicable diseases (NCDs), with increased overall NCD proportional mortality over the past two decades. The disease burden of mental health increased, resulting from rapid ageing, enhanced stress, and the COVID-19 pandemic, but it was largely neglected. The highly diverse cultures, religions, political systems, socioeconomic contexts, lifestyles, and environmental factors probably have led to massive disparities across countries in NCD mortality, risk factors, and NCD management. Geographically, East Asia had the lowest NCD mortality whilst Pacific islands had the highest. Economic booms, ageing, nutrition transition, social stress, prevalent tobacco use, and fast-increasing obesity and hyperglycaemia are important drivers of NCDs. Men tended to have more adverse behavioural and metabolic risk factors. Rural residents are catching up with their urban counterparts in metabolic risk factors and conditions. Sustainable strategies tailored to NCD patterns are needed to fight the NCD epidemic and related disparities.

Excessive fructose diet is closely associated with colorectal cancer (CRC) progression. Nevertheless, fructose's specific function and precise mechanism in colorectal cancer liver metastasis (CRLM) is rarely known. Here, this study reported that the fructose absorbed by primary colorectal cancer could accelerate CRLM, and the expression of KHK-A, not KHK-C, in liver metastasis was higher than in paired primary tumors. Furthermore, KHK-A facilitated fructose-dependent CRLM in vitro and in vivo by phosphorylating PKM2 at Ser37. PKM2 phosphorylated by KHK-A inhibited its tetramer formation and pyruvic acid kinase activity but promoted the nuclear accumulation of PKM2. EMT and aerobic glycolysis activated by nuclear PKM2 enhance CRC cells' migration ability and anoikis resistance during CRLM progression. TEPP-46 treatment, targeting the phosphorylation of PKM2, inhibited the pro-metastatic effect of KHK-A. Besides, c-myc activated by nuclear PKM2 promotes alternative splicing of KHK-A, forming a positive feedback loop.

Objective: To explore the scope of metabolic syndrome (MetS) and its relationship to the major dietary patterns among an urbanised and semi-urbanised Tibetan population in transition from nomadic to settled settings.Design: Cross-sectional.Setting: Community-based.Participants: Urbanised and semi-urbanised Tibetan adults (n 920, aged 18–90 years), who have moved from nomadic to settled living environments, answered questionnaires on food consumption frequency and lifestyle characteristics through structured face-to-face interviews and completed anthropometric measurement and metabolic biomarker tests.Results: MetS prevalence was 30·1 % in males and 32·1 % in females. Low HDL-cholesterol and central obesity were the leading metabolic abnormalities (86·3 and 55·8 %, respectively). Three major dietary patterns – urban, western and pastoral – were identified. Beef/mutton was an important food group for all three identified dietary patterns. In addition, the urban dietary pattern was characterised by frequent consumption of vegetables, tubers/roots and refined carbohydrates; the western pattern was characterised by sweetened drinks, snacks and desserts; and the pastoral pattern featured tsamba (roasted Tibetan barley), Tibetan cheese, butter tea/milk tea and whole-fat dairy foods. Individuals in the highest quintile of urban dietary pattern scores were found to be at a higher risk of developing MetS (OR 2·43, 95 % CI 1·41, 4·18) and central obesity (OR 1·91, 95 % CI 1·16, 3·14) after controlling for potential confounders.Conclusions: MetS was common among urbanised and semi-urbanised Tibetan adult population in transition. The urban dietary pattern, in particular, was a risk factor for MetS. To prevent MetS, nutrition interventions need to be tailored to address the variety of local diet patterns to promote healthy eating.

Cardiometabolic diseases (CMDs) are the major types of non-communicable diseases, contributing to huge disease burdens in the Western Pacific region (WPR). The use of digital health (dHealth) technologies, such as wearable gadgets, mobile apps, and artificial intelligence (AI), facilitates interventions for CMDs prevention and treatment. Currently, most studies on dHealth and CMDs in WPR were conducted in a few high- and middle-income countries like Australia, China, Japan, the Republic of Korea, and New Zealand. Evidence indicated that dHealth services promoted early prevention by behavior interventions, and AI-based innovation brought automated diagnosis and clinical decision-support. dHealth brought facilitators for the doctor-patient interplay in the effectiveness, experience, and communication skills during healthcare services, with rapidly development during the pandemic of coronavirus disease 2019. In the future, the improvement of dHealth services in WPR needs to gain more policy support, enhance technology innovation and privacy protection, and perform cost-effectiveness research.

(1) Background: We investigated the effects of a 12-week exercise intervention with or without vitamin D supplementation on insulin resistance and the plasma lipidome of participants with type 2 diabetes. We further explored whether the effects of the intervention on glycemic parameters could be associated with the baseline lipidome. (2) Methods: Sixty-one participants were randomly allocated to control (Con), exercise (EX), vitamin D (VD), and EX + VD groups. Multiple glycemic and anthropometric parameters were evaluated before and after intervention. The homeostasis model assessment of insulin resistance (HOMA-IR) was the primary outcome. The plasma lipidome was analyzed before, after, and at an additional 12-week follow-up. Machine learning was applied to establish prediction models for responsiveness of glycemic control. (3) Results: Our interventions failed to improve the HOMA-IR index while fasting glucose was reduced in the EX + VD group (change%, −11.9%; effect size, 0.65; p < 0.05). Both EX and VD interventions altered the plasma lipidome, with EX + VD intervention considerably affecting levels of lyso-phosphatidylcholines and triglycerols containing long-chain unsaturated fatty acids. Such effects could last until 12 weeks after intervention. Notably, there was high inter-individual variability in glycemic parameters including HOMA-IR in response to the interventions, which could be predicted with great accuracy using an optimal panel of baseline lipid predictors alone or in combination with clinical indices, as assessed by an area under the receiver operating characteristic curve value of over 0.9. (4) Conclusions: Although substantial alterations were observed in the plasma lipidome related to glycemic control, our intervention failed to improve HOMA-IR scores, which may have been predominately due to the large inter-individual variability in responses. Basal plasma lipid levels could potentially predict an individual’s response to intervention, highlighting the necessity of personalized nutrition.