Type 2 Diabetes Mellitus (T2DM) is a chronic disease closely related to personal life style. Therefore, achieving effective self-management is one of the most important ways to control it. There is evidence that social support can help to improve the self-management ability of patients with T2DM, but which social support is more effective has been rarely explored. The purpose of this study is to construct an integrated model to analyze which social support has more significant impact on self-management of T2DM, and provide reasonable suggestions to health care providers on how to effectively play the role of social support. We established a social support indicator evaluation system and proposed an integrated model that combines ANP (Analytical Network Process) and CRITIC (CRiteria Importance through Intercriteria Correlation) methods to evaluate the impact of social support on T2DM self-management from both subjective and objective perspectives. The weights calculated by the model will serve as the basis for us to judge the importance of different social support indicators. Informational support (weighting 49.26%) is the most important criteria, followed by tangible support (weighting 39.24%) and emotional support (weighting 11.51%). Among 11 sub-criteria, guidance (weighting 23.05%) and feedback (weighting 14.68%) are two most relevant with T2DM self-management. This result provides ideas and evidence for health care providers on how to offer more effective social support. To our knowledge, this is the first study in which Multi-Criteria Decision Making (MCDM) tools, specifically ANP and CRITIC, are used to evaluate the impact of social support on improving self-management of type 2 diabetes. The study suggests that incorporating two sub-indicators of guidance and feedback into the diabetes care programs may have great potential to improve T2DM self-management and further control patient blood glucose and reduce complications.

To explore the effects of celecoxib on pressure overload‐induced cardiac hypertrophy (CH), cardiac dysfunction and explore the possible protective mechanisms. We surgically created abdominal aortic constrictions (AAC) in rats to induce CH. Rats with CH symptoms at 4 weeks after surgery were treated with celecoxib [2 mg/100 g body‐weight(BW)] daily for either 2 or 4 weeks. Survival rate, blood pressure and cardiac function were evaluated after celecoxib treatment. Animals were killed, and cardiac tissue was examined for morphological changes, cardiomyocyte apoptosis, fibrosis, inflammation and oxidative stress. Four weeks after AAC, rats had significantly higher systolic, diastolic and mean blood pressure, greater heart weight and enlarged cardiomyocytes, which were associated with cardiac dysfunction. Thus, the CH model was successfully established. Two weeks later, animals had impaired cardiac function and histopathological abnormalities including enlarged cardiomyocytes and cardiac fibrosis, which were exacerbated 2 weeks later. However, these pathological changes were remarkably prevented by the treatment of celecoxib, independent of preventing hypertension. Mechanistic studies revealed that celecoxib‐induced cardiac protection against CH and cardiac dysfunction was due to inhibition of apoptosis via the murine double mimute 2/P53 pathway, inhibition of inflammation via the AKT/mTOR/NF‐κB pathway and inhibition of oxidative stress via increases in nuclear factor E2‐related factor‐2‐mediated gene expression of multiple antioxidants. Celecoxib suppresses pressure overload‐induced CH by reducing apoptosis, inflammation and oxidative stress.

Tuberculosis (TB) is an important public health issue worldwide. However, evidence concerning the impact of environmental factors on TB is sparse. We performed a retrospective analysis to determine the spatiotemporal trends and geographic variations of, and the factors associated with, the TB prevalence in Inner Mongolia. We performed a retrospective analysis of the epidemiology of TB. A Bayesian spatiotemporal model was used to investigate the spatiotemporal distribution and trends of the TB prevalence. A spatial panel data model was used to identify factors associated with the TB prevalence in the 101 counties of Inner Mongolia, using county-level aggregated data collected by the Inner Mongolia Center for Disease Control and Prevention. From January 2010 to December 2014, 79,466 (6.36‱) incident TB cases were recorded. The TB prevalence ranged from 4.97‱ (12,515/25,167,547) in 2014 to 7.49‱ (18,406/ 24,578,678) in 2010; the majority of TB cases were in males, and in those aged 46–60 years; by occupation, farmers and herdsmen were the most frequently affected. The Bayesian spatiotemporal model showed that the overall TB prevalence decreased linearly from 2010 to 2014 and occupation-stratified analyses yielded similar results, corroborating the reliability of the findings. The decrease of TB prevalence in the central-western and eastern regions was more rapid than that in the overall TB prevalence. A spatial correlation analysis showed spatial clustering of the TB prevalence from 2011 to 2014 (Moran’s index > 0, P < 0.05); in the spatial panel data model, rural residence, birth rate, number of beds, population density, precipitation, air pressure, and sunshine duration were associated with the TB prevalence. The overall TB prevalence in Inner Mongolia decreased from 2010 to 2014; however, the incidence of TB was high throughout this period. The TB prevalence was influenced by a spatiotemporal interaction effect and was associated with epidemiological, healthcare, and environmental factors.

Hypertension is a major risk factor for the global burden of disease, particularly in countries that are not economically developed. This study aimed to evaluate risk factors associated with self-reported hypertension among residents of Inner Mongolia using a cross-sectional study and to explore trends in the rate of self-reported hypertension. Multi-stage stratified cluster sampling was used to survey 13,554 participants aged more than 15 years residing in Inner Mongolia for the 2013 Fifth Health Service Survey. Hypertension was self-reported based on a past diagnosis of hypertension and current use of antihypertensive medication. Adjusted odds risks (ORs) of self-reported hypertension were derived for each independent risk factor including basic socio-demographic and clinical factors using multivariable logistic regression. An optimized risk score model was used to assess the risk and determine the predictive power of risk factors on self-reported hypertension among Inner Mongolia residents. During study period, self-reported hypertension prevalence was 19.0% (2571/13,554). In multivariable analyses, both female and minority groups were estimated to be associated with increased risk of self-reported hypertension, adjusted ORs (95% CI) were 1.22 (1.08, 1.37) and 1.66 (1.29, 2.13) for other minority compared with Han, increased risk of self-reported hypertension prevalence was associated with age, marital status, drinking, BMI, and comorbidity. In the analyses calculated risk score by regression coefficients, old age (≥71) had a score of 12, which was highest among all examined factors. The predicted probability of self-reported hypertension was positively associated with risk score. Of 13,421 participants with complete data, 284 had a risk score greater than 20, which corresponded to a high estimated probability of self-reported hypertension (≥67%). Self-reported hypertension was largely related to multiple clinical and socio-demographic factors. An optimized risk score model can effectively predict self-reported hypertension. Understanding these factors and assessing the risk score model can help to identify the high-risk groups, especially in areas with multi-ethnic populations.

BACKGROUND:The aim of this study was to investigate the effects of TNF-α and IL-10 on the expression of ICAM-1 and CD31 in human coronary artery endothelial cells (HCAEC). MATERIAL AND METHODS:HCAEC was treated with 0, 2.5 μg/l, 5 μg/l, and 10 μg...