Aims: To examine the incidence of cardiovascular disease (CVD) and mortality in China and in key subpopulations, and to estimate the population-level risks attributable to 12 common modifiable risk factors for each outcome.Methods and results: In this prospective cohort of 47 262 middle-aged participants from 115 urban and rural communities in 12 provinces of China, it was examined how CVD incidence and mortality rates varied by sex, by urban-rural area, and by region. In participants without prior CVD, population-attributable fractions (PAFs) for CVD and for death related to 12 common modifiable risk factors were assessed: four metabolic risk factors (hypertension, diabetes, abdominal obesity, and lipids), four behavioural risk factors (tobacco, alcohol, diet quality, and physical activity), education, depression, grip strength, and household air pollution. The mean age of the cohort was 51.1 years. 58.2% were female, 49.2% were from urban areas, and 59.6% were from the eastern region of China. The median follow-up duration was 11.9 years. The CVD was the leading cause of death in China (36%). The rates of CVD and death were 8.35 and 5.33 per 1000 person-years, respectively, with higher rates in men compared with women and in rural compared with urban areas. Death rates were higher in the central and western regions of China compared with the eastern region. The modifiable risk factors studied collectively contributed to 59% of the PAF for CVD and 56% of the PAF for death in China. Metabolic risk factors accounted for the largest proportion of CVD (PAF of 41.7%), and hypertension was the most important risk factor (25.0%), followed by low education (10.2%), high non-high-density lipoprotein cholesterol (7.8%), and abdominal obesity (6.9%). The largest risk factors for death were hypertension (10.8%), low education (10.5%), poor diet (8.3%), tobacco use (7.5%), and household air pollution (6.1%).Conclusion: Both CVD and mortality are higher in men compared with women, and in rural compared with urban areas. Large reductions in CVD could potentially be achieved by controlling metabolic risk factors and improving education. Lowering mortality rates will require strategies addressing a broader range of risk factors.

OBJECTIVE Previous prospective studies on the association of white rice intake with incident diabetes have shown contradictory results but were conducted in single countries and predominantly in Asia. We report on the association of white rice with risk of diabetes in the multinational Prospective Urban Rural Epidemiology (PURE) study. RESEARCH DESIGN AND METHODS Data on 132,373 individuals aged 35–70 years from 21 countries were analyzed. White rice consumption (cooked) was categorized as <150, ≥150 to <300, ≥300 to <450, and ≥450 g/day, based on one cup of cooked rice = 150 g. The primary outcome was incident diabetes. Hazard ratios (HRs) were calculated using a multivariable Cox frailty model. RESULTS During a mean follow-up period of 9.5 years, 6,129 individuals without baseline diabetes developed incident diabetes. In the overall cohort, higher intake of white rice (≥450 g/day compared with <150 g/day) was associated with increased risk of diabetes (HR 1.20; 95% CI 1.02–1.40; P for trend = 0.003). However, the highest risk was seen in South Asia (HR 1.61; 95% CI 1.13–2.30; P for trend = 0.02), followed by other regions of the world (which included South East Asia, Middle East, South America, North America, Europe, and Africa) (HR 1.41; 95% CI 1.08–1.86; P for trend = 0.01), while in China there was no significant association (HR 1.04; 95% CI 0.77–1.40; P for trend = 0.38). CONCLUSIONS Higher consumption of white rice is associated with an increased risk of incident diabetes with the strongest association being observed in South Asia, while in other regions, a modest, nonsignificant association was seen.

Background: The predictive value of adiposity indices and the newly developed index for cardiometabolic risk factors and cardiovascular diseases ( CVD s) remains unclear in the Chinese population. This study aimed to compare the predictive value of A Body Shape Index with other 5 conventional obesity‐related anthropometric indices (body mass index, waist circumference, hip circumference, waist‐to‐hip ratio, waist‐to‐height ratio) in Chinese population. Methods and Results: A total of 44 048 participants in the study were derived from the baseline data of the PURE ‐China (Prospective Urban and Rural Epidemiology) study in China. All participants’ anthropometric parameters, CVD s, and risk factors (dyslipidemia, abnormal blood pressure, and hyperglycemia) were collected by standard procedures. Multivariable logistic regression models and receiver operator characteristic curve analysis were used to evaluate the predictive values of obesity‐related anthropometric indices to the cardiometabolic risk factors and CVD s. A positive association was observed between each anthropometric index and cardiometabolic risk factors and CVD s in all models ( P <0.001). Compared with other anthropometric indices (body mass index, waist circumference, hip circumference, waist‐to‐hip ratio, and A Body Shape Index), waist‐to‐height ratio had significantly higher areas under the curve ( AUC s) for predicting dyslipidemia ( AUC s: 0.646, sensitivity: 65%, specificity: 44%), hyperglycemia ( AUC s: 0.595, sensitivity: 60%, specificity: 45%), and CVD s ( AUC s: 0.619, sensitivity: 59%, specificity: 41%). Waist circumference showed the best prediction for abnormal blood pressure ( AUC s: 0.671, sensitivity: 66%, specificity: 40%) compared with other anthropometric indices. However, the new body shape index did not show a better prediction to either cardiometabolic risk factors or CVD s than that of any other traditional obesity‐related indices. Conclusions: Waist‐to‐height ratio appeared to be the best indicator for dyslipidemia, hyperglycemia, and CVD s, while waist circumference had a better prediction for abnormal blood pressure.

Increased sitting time has become common in modern society owing to the popularization of electronic products, an increase in sedentary occupations, and changing patterns of transportation. Serial analyses reported total sitting time has substantially increased by nearly 1 hour per day among adults over the past decade in the US.^1,2 The recent World Health Organization (WHO) 2020 global physical activity guideline now recommends limiting sedentary time and engaging in high levels of physical activity to reduce the detrimental effects of sitting time.³

Although socioeconomic inequality in cardiovascular health has long been a public health focus, the differences in cardiovascular-disease burden and mortality between people with different socioeconomic statuses has yet to be adequately addressed. We aimed to assess the effects of socioeconomic status, measured via three socioeconomic-status indicators (ie, education, occupation, and household wealth and a composite socioeconomic-status disparity index, on mortality and cardiovascular-disease burden (ie, incidence, mortality, and admission to hospital) in China. For this analysis, we used data from the Prospective Urban Rural Epidemiology (PURE)-China cohort study, which enrolled adults aged 35-70 years from 115 urban and rural areas in 12 provinces in China between Jan 1, 2005, and Dec 31, 2009. Final follow-up was on Aug 30, 2021. Indicators of socioeconomic status were education, occupation, and household wealth; these individual indicators were also used to create an integrated socioeconomic-status index via latent class analysis. Standard questionnaires administered by trained researchers were used to obtain baseline data and were supplemeted by physical measurements. The primary outcomes were all-cause mortality, cardiovascular-disease mortality, non-cardiovascular-disease mortality, major cardiovascular disease, and cardiovascular-disease admission to hospital. Hazard ratios (HRs) and average marginal effects were used to assess the association between the primary outcomes and socioeconomic status. Of 47 931 participants enrolled in the PURE-China study, 47 278 (98·6%) had complete information on sex and follow-up. After excluding 1189 (2·5%) participants with missing data on education, household wealth, and occupation at baseline, 46 089 participants were included in this analysis. Median follow-up was 11·9 years (IQR 9·5-12·6); 26 860 (58·3%) of 46 089 participants were female and 19 229 (41·7%) were male. Having no or primary education, unskilled occupation, or being in the lowest third of household wealth was associated with a higher risk of all-cause mortality, cardiovascular-disease mortality, non-cardiovascular-disease mortality, major cardiovascular disease, and cardiovascular-disease admission to hospital compared with having higher education, a professional or managerial occupation, or more household wealth. After adjustment for confounders, people categorised as having low integrated socioeconomic status based on the index had a higher risk of all-cause mortality (HR 1·65 [95% CI 1·42-1·92]), cardiovascular-disease mortality (2·19 [1·68-2·85]), non-cardiovascular disease mortality (1·43 [1·18-1·72]), major cardiovascular disease (1·43 [1·27-1·61]) and cardiovascular-disease admission to hospital (1·14 [1·01-1·28]) compared with people categorised as having high integrated socioeconomic status. Socioeconomic-status inequalities in mortality and cardiovascular-disease outcomes exist in China. Targeted policies of equal health-care resource allocation should be promoted to equitably benefit people with fewer years of education and less household wealth. Funding sources are listed at the end of the Article.

Background: Most cardiovascular diseases occur in low‐ and middle‐income regions of the world, but the socioeconomic distribution within China remains unclear. Our study aims to investigate whether the prevalence of cardiovascular diseases differs among high‐, middle‐, and low‐income regions of China and to explore the reasons for the disparities. Methods and Results: We enrolled 46 285 individuals from 115 urban and rural communities in 12 provinces across China between 2005 and 2009. We recorded their medical histories of cardiovascular diseases and calculated the INTERHEART Risk Score for the assessment of cardiovascular risk‐factor burden, with higher scores indicating greater burden. The mean INTERHEART Risk Score was higher in high‐ and middle‐income regions than in low‐income regions (9.47, 9.48, and 8.58, respectively, P <0.0001). By contrast, the prevalence of total cardiovascular disease (stroke, ischemic heart disease, and other heart diseases that led to hospitalization) was lower in high‐ and middle‐income regions than in low‐income regions (7.46%, 7.42%, and 8.36%, respectively, P _trend =0.0064). In high‐ and middle‐income regions, urban communities have higher INTERHEART Risk Score and higher prevalent rate than rural communities. In low‐income regions, however, the prevalence of total cardiovascular disease was similar between urban and rural areas despite the significantly higher INTERHEART Risk Score for urban settings. Conclusions: We detected an inverse trend between risk‐factor burden and cardiovascular disease prevalence in urban and rural communities in high‐, middle‐, and low‐income regions of China. Such asymmetry may be attributed to the interregional differences in residents’ awareness, quality of healthcare, and availability and affordability of medical services.