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Purpose: To address the prevalence of diabetes distress (DD) and its correlators in adults with type 2 diabetes.Patients and Methods: During 2021 and 2022, we conducted a cross-sectional study in three Class A tertiary comprehensive hospitals in China, and received 947 participants who completed a printed survey covering DD, demographic, diabetic, physiological, and psychosocial factors. We used Jonckheere-Terpstra, chi-square, and Fisher's exact tests to assess intergroup differences between different levels of DD. We used ordinal logistic regression analysis to analyze correlators of DD further.Results: The prevalence of DD was 34.64%. In univariate analysis, those with lower satisfaction with financial status, longer durations of diabetes, more complications, higher glycemia, more severe insomnia, treatment by medications only, poorer lifestyle interventions, fewer self-care activities, more types and frequencies of insulin injections, and spending more money and time on treatment were susceptible to DD. Type D personality, negative illness perceptions, negative coping styles, and psychological effects of major life events were related to higher DD. Hope, self-efficacy, positive coping styles, and social support can reduce DD. In ordinal logistic regression analysis, hypoglycemic episode (β=− 1.118, p=0.019, "have hypoglycemic" as reference) and Brief Illness Perception Questionnaire (β=0.090, p< 0.001) were significant positive correlators for DD, while diet intervention (β=0.803, p=0.022, "have diet intervention" as reference), money spent on diabetes treatment (β<-0.001,>p=0.035), and SES (β=− 0.257, p< 0.001) were significant negative correlators.Conclusion: More than one-third of Chinese adults with type 2 diabetes experience moderate or high levels of DD. DD was associated with financial, diabetic, physiological, and psychosocial status. [ABSTRACT FROM AUTHOR]

Understanding the spatial–temporal evolution of the blue–green space (BGS) is crucial for urban planning and ecological security protection. However, the evolutionary patterns and driving factors of the BGS in new urban districts remain unclear. Based on the classical qualitative models, "patch–corridor–matrix" and "sustainability prism", this study adopted the land use transition matrix and landscape index to quantify evolution patterns, and Pearson correlation and geographical detector analysis methods to reveal the driving factors. Taking Zhengdong New District as a case study, the results indicated the following: (1) The BGS rate was reduced by 35% from 2003 to 2021, with the most significant decrease in cultivated lands. (2) The evolution pattern of BGS alternated sequentially among ecological, disorderly, and balanced states. Among them, urban green spaces tended towards a more stable and aggregated state. Other BGSs became more fragmented and discontinuous. (3) The "sustainability prism" model consists of four driving factors, including social economy, rainwater safety, ecological liveability, and physical geography. (4) Socioeconomic factors significantly decreased the BGS, as indicated by the correlation coefficients of −0.988 and −0.978 between built-up areas and population and gross domestic products, respectively. Physical geographic factors played weak roles in the evolution of the BGS. Meanwhile, rainwater safety and ecological liveability positively affected the BGS. [ABSTRACT FROM AUTHOR]

Exploring the temporal and spatial changes, as well as driving factors, of net primary productivity (NPP) of terrestrial ecosystems is essential for maintaining regional carbon balance. This work focuses on the spatiotemporal variation and future trends of NPP and the response mechanisms of NPP to various driving factors. The Theil–Sen estimator, as well as Mann–Kendall and Hurst exponent methods, were used to analyze the spatiotemporal dynamics and future trends of NPP, and geographical detectors and correlation analysis were used to reveal the response of NPP to various driver changes to environmental factors. The results showed that the NPP was generally on an increasing trend in the Yangtze River Delta region from 2000 to 2019, with the average NPP value of 550.17 g C m−2 a−1, of which 85.90% was the increasing regions and 14.10% was the decreasing regions, showing a significant spatiotemporal heterogeneity characteristic. The trend of future changes in NPP is dominated by an anti-persistence trend in the study area, i.e., the opposite of the past trend. Notably, annual precipitation is the most significant positive driver of NPP; while NPP was negatively correlated with population, meanwhile, different land use/land cover (LULC) also significantly affected the spatial distribution of NPP. Besides, there was a two-factor enhanced interaction between the various drivers on NPP, with the highest interaction occurring between temperature and elevation. Overall, this study provides data support for future regional NPP predictions and ecosystem evaluations. [ABSTRACT FROM AUTHOR]

Background: A remarkable drop in tuberculosis (TB) incidence has been achieved in China, although in 2019 it was still considered the second most communicable disease. However, TB's spatial features and risk factors in urban areas remain poorly understood. This study aims to identify the spatial differentiations and potential influencing factors of TB in highly urbanized regions on a fine scale. Methods: This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou, China. TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention. Before using Pearson correlation and a geographical detector (GD) to identify potential influencing factors, we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales. Results: Owing to its strong spatial autocorrelation (Moran's I = 0.33, Z = 4.71), the 2 km × 2 km grid was selected as the spatial scale. At this level, TB incidence was closely associated with most socioeconomic variables (0.31 < r < 0.76, P < 0.01). Of five environmental factors, only the concentration of fine particulate matter displayed significant correlation (r = 0.21, P < 0.05). Similarly, in terms of q values derived from the GD, socioeconomic variables had stronger explanatory abilities (0.08 < q < 0.57) for the spatial differentiation of the 2017 incidence of TB than environmental variables (0.06 < q < 0.27). Moreover, a much larger proportion (0.16 < q < 0.89) of the spatial differentiation was interpreted by pairwise interactions, especially those (0.60 < q < 0.89) related to the 2016 incidence of TB, officially appointed medical institutions, bus stops, and road density. Conclusions: The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably influenced by several socioeconomic and environmental factors and their pairwise interactions on a fine scale. We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou. Our study provides helpful clues for local authorities implementing more effective intervention measures to reduce TB incidence in China's municipal areas, which are featured by both a high degree of urbanization and a high incidence of TB. [ABSTRACT FROM AUTHOR]

Background: It is well known that unexpected pandemic has led to an increase in mental health problems among a variety of populations.Methods: In this study, an online non-probability sample survey was used to anonymously investigate the anxiety and depression symptoms among medical staff under the COVID-19 outbreak. The questionnaire included Perceived Stress Scale-10 (PSS-10), Generalized Anxiety Disorder 7-Item Scale (GAD-7) and Patient Health Questionnaire-9 (PHQ-9). Factors associated with anxiety and depression symptoms were estimated by logistic regression analysis.Results: A total of 1090 medical staff were investigated in this study. The estimated self-reported rates of anxiety symptoms, depression symptoms and both of the two were 13.3%, 18.4% and 23.9% respectively. Factors associated with self-reported anxiety symptoms include married status (OR=2.3, 95%CI: 1.2, 4.4), not living alone (OR=0.4, 95%CI: 0.2, 0.7), never confiding their troubles to others (OR=2.2, 95%CI: 1.4, 3.5) and higher stress (OR=14.4, 95%CI: 7.8, 26.4). Factors associated with self-reported depression symptoms include not living alone (OR=0.4, 95%CI: 0.3, 0.7), sometimes/often getting care from neighbours (OR=0.6, 95%CI: 0.4, 0.9), never confiding their troubles to others (OR=2.0, 95%CI: 1.3, 3.0) and higher stress (OR=9.7, 95%CI: 6.2, 15.2).Limitations: The study was a non-probability sample survey. Besides, scales used in this study can only identify mental health states.Conclusions: Under outbreak of COVID-19, self-reported rates of anxiety symptoms and depression symptoms were high in investigated medical staff. Psychological interventions for those at high risk with common mental problems should be integrated into the work plan to fight against the epidemic. [ABSTRACT FROM AUTHOR]

Comparisons are made of the performance of a correlation detector compared to a standard short-term average window/long-term average window (STA/LTA) detector for 90 events in the 1999 Xiuyan, China, earthquake sequence. Triggers on three component data verify independent detections to the nearest sample. Unrelated signals that trigger above a threshold do not align on the three components and do not constructively interfere when the cross-correlation traces are stacked or averaged. Semi-similar events due to less than perfect matches arising from substantial mechanism differences can provide useful detections. Synthetic tests on 78 028 focal mechanisms indicate that statistically significant detections are still triggered for strike, dip and rake variations as large as 55°. The correlation detector finds 90 out of 90 or 100 per cent of the events whereas a STA/LTA detector finds 10 out of 90 or 11 per cent. This represents a 1.3 magnitude unit reduction in detection threshold for these events or nearly a factor of 20 improvement. [ABSTRACT FROM AUTHOR]