Mediating effect of gastrointestinal symptoms on dietary behavior and quality of life in Chinese adults with chronic gastritis-a cross-sectional study.

Background: Chronic gastritis is accompanied by varying degrees of gastrointestinal symptoms, which affect people's quality of life. The association between dietary behaviors and gastrointestinal symptoms of patients with chronic gastritis has been proved recently. However, no studies have been conducted to investigate the relationship between dietary behaviors, gastrointestinal symptoms, and quality of life. Methods: A cross-sectional survey of 176 patients diagnosed with chronic gastritis aged 18 to 65 years, comprising their information on demographic characteristics, dietary behaviors, gastrointestinal symptoms, and quality of life, was collected. A descriptive analysis and a correlation matrix were used to illuminate the characteristics of the subjects and bivariate correlation, respectively. The mediation model was analyzed using the PROCESS macros for SPSS. Results: Demographic characteristics were found to influence the symptoms, dietary behaviors, and quality of life of chronic gastritis patients; in particular, students categorized by occupation had higher levels of gastrointestinal symptoms and lower levels of quality of life and dietary behavior. The study variables were all pound related. We found that gastrointestinal symptoms played a partial mediating role between dietary behavior and both the physical components summary and mental components summary, and the ratios of mediating effects to the total effect on the physical components summary and mental components summary were 23.5% and 21.5%, respectively. Conclusion: Our survey discovered that dietary behavior, gastrointestinal symptoms, and quality of life were all pairwise related. The effect of dietary behavior on quality of life was partially mediated by gastrointestinal symptoms. These results may provide a novel perspective for medical staff in improving the quality of life of patients with chronic gastritis.

Scenario simulations for the peak of provincial household CO2 emissions in China based on the STIRPAT model.

As household CO2 emissions (HCEs) are a key source of China's CO2 emissions, exploring the mitigation potential of HCEs is significant to achieve China's 2030 emission target. However, rare literatures analyzed the future evolution of HCEs from the provincial perspective. Here, we employ the STIRPAT model and build three scenarios (i.e., baseline, low and high scenarios) to investigate the trajectories and peak times of HCEs in 30 provinces up to 2040. The results show that 25 provinces can peak HCEs before 2030 in at least one scenario, while 5 provinces cannot achieve the 2030 emission target in any scenarios. Moreover, Guangxi and Hainan will maintain growth up to 2040 in all three scenarios. At the national level, China's household sector can achieve HCEs peak in all three scenarios. Further reduction of emission intensity helps national HCEs reach the peak around 2025 in the high scenario at 1063 MtCO2. The findings suggest that Guangdong, Jiangsu, Hebei, Henan, Zhejiang and Anhui are key provinces for future HCEs reductions, because they account for more than 40% of national HCEs in 2040 in all three scenarios. Energy efficiency improvement and clean energy applications will be effective for emission reductions.

Factors driving the change of household CO2 emissions through 2040 in China: based on decomposition and scenario analyses.

With China's economic transformation into a consumption-driven model, household CO2 emissions (HCEs) become an increasingly essential part of China's CO2 emissions. However, how will the HCEs change in urban and rural areas and what are the driving forces of HCEs through 2040 are not clear. In this paper, we project nation-level HCEs up to 2040 by the scenario analysis, and analyze the drivers of HCEs during 1997-2040 by the decomposition analysis. We find that the HCEs kept a persistent growth during 1997-2017 as energy intensity reduction and energy structure optimization cannot offset the rapid growth of consumption and population. During 2017-2040, in the current policy scenario, the rural HCEs will decrease, while the peaking of the total HCEs and urban HCEs would not be achieved. In the sustainable development scenario, the total HCEs, urban HCEs and rural HCEs will peak before 2030 and afterward decrease, because the energy intensity will induce a 51% and 76% reduction in the total HCEs and urban HCEs, respectively. Moreover, the decrease in the share of coal consumption due to the development of non-fossil fuels and natural gas will cause a more than 25% reduction in HCEs in the sustainable development scenario.

Understanding regional inequality in per capita CO2 emissions in China during 1997-2016: sources and driving factors.

As the largest carbon dioxide (CO2) emitter, China exists obvious regional inequality in per capita CO2 emissions. However, such inequality and its dynamic change for recent years have not been systematically studied. In this paper, we evaluate China's regional inequality in per capita CO2 emissions during 1997-2016 using the Theil index and decompose it into within-region and between-region components based on eight regions. Furthermore, we apply the decomposition analysis to explore the contribution of different factors to such inequality, including the carbonization index, energy intensity, energy structure, labor productivity, and employment rate. The results show that China's overall inequality in per capita CO2 emissions reduced first and increased thereafter during 1997-2016. Within-region inequality was the main source of overall inequality in 1997-2004, while between-region inequality contributed more during 2005-2016. Labor productivity and energy intensity were the two main drivers of overall inequality, but their contributions to the inequality between regions and within regions were quite different. Moreover, the impact of energy structure and carbonization index on regional inequality in per capita CO2 emissions significantly increased during 2012-2016, which was related to the efforts made by local governments to improve the energy mix. Policy implications were given according to the above conclusions to improve regional inequality in per capita CO2 emissions.