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Importance: Sleep duration plays an important role in predicting CCVD incidence, and have implications for reducing the burden of CCVD. However, the association between sleep duration and predicted cardio-cerebral vascular diseases (CCVD) risk remains to be fully understood. Objective: To investigate the effects of sleep duration on the development of CCVD among Chinese community residents. Design: A prospective cohort study. The baseline survey was conducted from January 2013 to July 2013. The cohort has been followed until December 31, 2016 using a combination of in-person interviews and record linkages with the vital registry of Pudong New Area, Shanghai, China. Subjects: A total of 8245 Chinese community residents were initially enrolled in the cohort. Of those, 6298 underwent the follow-up examination. Exposure: Self-reported sleep duration and sleep quality were obtained via the questionnaire. Sleep duration was divided into five categories: ≤5, 6, 7, 8, or ≥ 9 h per day. Main Outcome(s) and Measure(s): CCVD, Coronary heart disease (CHD) and Stroke occurrence, Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated using Fine-Gray proportional subdistribution hazards models. Results: During a median follow-up of 3.00 years (IQR 2.92–3.08), we observed 370 participants have had incident CCVD events, of whom 230 had CHDs, 169 had strokes, and 29 had both. After adjustment for relevant confounders, short sleepers (≤ 5 h) had 83% higher risk of total CCVD incidence (HR: 1.83; 95% CI: 1.32–2.54), 82% higher risk of CHD incidence (HR: 1.82; 95% CI: 1.21–2.75), and 82% higher risk of stroke incidence (HR: 1.82; 95% CI: 1.12–2.98) in contrast to the reference group (7 h). Some of these U-shaped relationships varied by age, and were more pronounced in individuals aged < 65 years. Individuals who slept ≤ 5 h per day with baseline hypertension had the highest risk of CCVD incidence (HR: 3.38, 95% CI 2.08–5.48), CHD incidence (HR: 3.11, 95% CI 1.75–5.53), and stroke incidence (HR: 4.33, 95% CI 1.90–9.86), compared with those sleep 7 h and without baseline hypertension. Conclusions: Short sleep duration is independently associated with greater incidence of CCVD, CHD and stroke. [ABSTRACT FROM AUTHOR]

Background: Cancer becomes the leading cause of premature death in China. Primary objective of this study was to determine the major risk factors especially glucose intolerance for cancer prophylaxis. Methods: A cluster sampling method was applied to enroll 10,657 community-based adults aged 15-92 years in Shanghai, China in 2013. A structured questionnaire and physical examination were applied in baseline survey. Prediabetes was diagnosed using 75-g oral glucose tolerance test. After excluding 1433 subjects including 224 diagnosed with cancer before and 1 year after baseline survey, the remaining 9,224 subjects were followed-up to December 31, 2020. Results: A total of 502 new cancer cases were diagnosed. The cancer incidence was 10.29, 9.20, and 5.95/1,000 person-years in diabetes patients, those with prediabetes, and healthy participants, respectively (p <0.001). The multivariate Cox regression analysis indicated that age, prediabetes and diabetes, were associated with an increased risk of cancer in those <65 years, the hazard ratios (95% confidence interval) for prediabetes and diabetes were, 1.49(1.09-2.02) and 1.51(1.12-2.02), respectively. Glucose intolerance (prediabetes and diabetes) were associated with increased risks of stomach cancer, colorectal cancer, and kidney cancer in those <65 years. Anti-diabetic medications reduced the risk of cancer caused by diabetes. The multivariate Cox analysis showed that age, male, <9 years of education, and current smoking were associated with increased risks of cancer in those ≥65 years independently. Conclusions: Glucose intolerance is the prominent cancer risk factor in adults <65 years. Lifestyle intervention and medications to treat glucose intolerance help prevent cancer in this population. [ABSTRACT FROM AUTHOR]

• We surveyed the driving factors of waste separation behavior (WSB) in Shanghai • We analyzed WSB based on the perspective of neighborhood spatial differentiation • We studied perceived grassroots governance effectiveness and information publicity • WSB differs between neighborhood types according to house price and age • This research can be used to formulate targeted waste separation policies Based on the theory of planned behavior, numerous driving forces of separation behavior have been demonstrated; however, spatial differentiation and information behavior warrant further investigation. This study focused on examining how internal factors (e.g., subjective norms, perceived behavioral control), external factors (e.g., perceived effectiveness of grass-roots governance (PGE), information publicity (IP)), and spatial differentiation factors affected waste separation behavior (WSB) in residents. Accordingly, a theoretical model was constructed to analyze 2555 valid questionnaires collected from 16 districts in Shanghai, revealing the following results: (1) Subjective norms and perceived behavioral control indirectly affect WSB only through offline behavioral intentions; (2) PGE and IP have direct and indirect effects on WSB through both on- and offline behavioral intentions; and, (3) Under the moderating effects of house prices and age in megacities, PGE and IP exhibited irregular and U-shaped effects, respectively. In addition, the results indicate spatial differences in WSB as a function of the neighborhood (stranger, acquaintance, and semi-acquaintance neighborhoods) and as a driving mechanism (weak mobilization–strong participation, strong mobilization–strong participation, and strong mobilization–weak participation). These findings provide a reference for formulating targeted waste separation policies, improving social mobilization mechanisms, ensuring timely information dissemination, and achieving sustainable household WSB. [ABSTRACT FROM AUTHOR]

[Display omitted] • Singapore kept its stale policy while targeting a zero-waste Circular Economy plan. • In 2019, Shanghai enhanced household waste segregation and recycling at the source. • Differences were assessed in strategy, environmental, economic and social perspectives. • New policies and digitalisation improved waste management in Shanghai in 2019. • Digitalisation, market reshaping and COVID-19 triggered challenges and opportunities. Due to rapid economic development and urbanisation, emerging megacities with dense populations have witnessed a significant increase in waste generation. Megacities face challenges in developing sustainable waste management systems. Considerable heterogeneity exists across megacities in management strategies. The two selected emerging megacities, Singapore (a city-state) and Shanghai, have similar developmental characteristics, but their waste management modes differ strikingly. This study assessed the two modes in terms of management strategies, environmental effects, economic costs, and social outcomes. Environmental footprint analysis and cost quantification were employed for the assessment based on public data. The research results would permit a deeper understanding of the long-term sustainability of each mode while considering the feasibility of implementation across different contexts. It was found that the waste management system in Singapore had a relatively lower environmental impact than Shanghai before Shanghai's new waste segregation and recycling policy in 2019. However, when the effect of fossil fuel substitution is taken into account, the environmental burden in Shanghai can be lowered more substantially than the one in Singapore. Although Shanghai had more economic burden for the waste segregation at source, it tended to implement the circular economy principles (e.g., reduce, reuse, and recycling) better and improve its sense of community significantly. Based on the practical experiences from the two representative megacities, suggestions for better waste management practices were provided for Singapore, Shanghai, and other emerging megacities with similar circumstances. In addition, challenges and opportunities related to household waste segregation and recycling were identified to guide future practices in emerging megacities. [ABSTRACT FROM AUTHOR]

• A flexible clustering approach is proposed for large-scale energy-water nexus. • Electricity-cooling-heating-water-hydrogen integrated model is built. • The flexibility of typical density-based spatial decomposition is improved. • Demand complementarity effect is considered during clustering. • The combined index assessment is integrated into the clustering and optimization. Modeling and optimization of a large-scale urban energy-water nexus system with sufficient spatial resolutions is a complex challenge. By proper clustering technique, a large-scale problem could possibly be divided into small ones with high spatial resolution and accuracy. Existing literature tends to lower the complexity of large-scale urban energy system problem by accumulating demand profiles on the spatial dimension. This study proposes a flexible clustering approach based on density clustering method with combined index assessment process. The flexible approach considers not only the spatial dimensions but also the complementarity effect of different demand profile and control the computational time of system design and optimization. The approach can increase the clustering flexibility by providing more clustering options than conventional method, take advantages of complementarity effect to further improve the system economic performance and control the solving time in an acceptable range. The proposed approach is evaluated by a case study of a new business district in Shanghai, China with a proposed future energy-water nexus system. After three combined index assessment, 45 new clustering maps are generated by the flexible clustering approach and the final optimal solution obtained by the proposed approach can further obtain 6.74% cost savings compared with conventional clustering approach. [ABSTRACT FROM AUTHOR]