[A cohort study on body mass index and risk of all-cause mortality among hypertensive population].

Objective: To investigate the relationship between body mass index (BMI) and all-cause mortality in hypertensive population. Methods: All participants were selected from a prospective cohort study based on a rural population from Henan province, China. Cox proportional hazards regression models were used to estimate the associations of different levels of BMI stratification with all-cause mortality. Restricted cubic spline models were used to detect the dose-response relation. Results: Among the 5 461 hypertensive patients, a total of 31 048.38 person-years follow-up was conducted. The median of follow-up time was 6 years, and 589 deaths occurred during the follow-up period. Compared to normal weight group (18.5 kg/m(2)

[Age-related modification effect on the association between body mass index and the risk of hypertension: A Cohort Study on Chinese people living in the rural areas].

Objective: To study the modification effect of age on the association between body mass index and the risk of hypertension. Methods: People age ≥18 years old were selected by clusters, from a rural area of Henan province. In total, 20 194 people were recruited at baseline during 2007 and 2008, and the follow-up study was completed from 2013 to 2014. Logistic regression model was used to assess the risk of incident hypertension by baseline BMI and age-specific BMI. Results: During the 6-year follow-up period, 1 950 hypertensive persons were detected, including 784 men and 1 166 women, with cumulative incidence rates as 19.96%, 20.51%, and 19.61%, respectively. Compared with those whose BMI<22 kg/m(2), the RRs of hypertension were 1.09 (0.93-1.27), 1.17 (1.01-1.37), 1.34 (1.14-1.58) and 1.31 (1.09-1.56) for participants with BMI as 22-, 24-, 26- and ≥28 kg/m(2), respectively. In young and middle-aged populations, the risk of hypertension gradually increased with the rise of BMI (trend P<0.05). However, in the elderly, the increasing trend on the risk of hypertension risk was not as significantly obvious (trend P>0.05). Conclusion: The effect of BMI on the incidence of hypertension seemed to depend on age. Our findings suggested that a weight reduction program would be more effective on young or middle-aged populations, to prevent the development of hypertension.

[Association between resting heart rate and metabolic syndrome: a cohort study].

Objective: To investigate the association between resting heart rate (RHR) and subsequent metabolic syndrome (MS). Methods: Under a cluster design, participants age ≥18 years old were selected from a rural area of Henan province in China. Interview through questionnaire, physical examination, fasting blood glucose, and lipid profile measurements were done from July to August of 2007 and July to August of 2008. Same methods were implemented in the follow-up examination, during July to August of 2013 and July to October of 2014. Results: During the 6-year follow-up period, cumulative incidence rates of MS for overall, male, and female participants appeared as 21.89%(1 933/8 829), 16.78%(664/3 957) and 26.05%(1 269/4 872), respectively. After controlling for potential confounders and compared with the groups of RHR<60 bpm, 60-69, 70-79, 80-89 and ≥90 bpm, the ORs (95%CIs) of MS for overall, male, and female participants became 1.24(0.95-1.60), 1.42(1.10-1.84), 1.63(1.24-2.15) and 1.62(1.16-2.27); 1.12(0.81-1.55), 1.23(0.88-1.71), 1.42 (0.97-2.07) and 1.84(1.09-3.11); 1.46(0.93-2.29), 1.70(1.09-2.65), 1.99(1.25-3.16) and 1.78(1.06-2.98); respectively. Conclusions: The risk on MS appeared higher in females than in males while the risk for MS increased with the elevation of RHR. Intensive intervention programs that targeted adult participants with elevated RHR, especially in females, should be formulated and implemented.

[Prevalence and risk factors of dyslipidemia in a rural population of Henan Province, China].

Objective: The purpose of this study was to investigate the prevalence and risk factors of dyslipidemia in a rural population of Henan Province, China. Methods: A total of 20 194 participants aged ≥18 years were selected randomly by cluster sampling from two townships(towns)in Henan Province from July to August 2007 and July to August 2008. Investigations included questionnaires, anthropometric measurements, fasting plasma glucose, and lipid profile examination at baseline. A total of 16 155 participants were followed up from July to August 2013 and July to October 2014. Overall, 13 869 participants were included in the study, after excluding 2 286 participants with incomplete dyslipidemia follow-up data. Distributions of the characteristics of dyslipidemia were determined, and prevalence was standardized by age according to data of the 2010 Sixth National Population Census. Risk factors for dyslipidemia were analyzed using a logistic regression model after adjusting for sex, age, education level, marital status, and income status. Results: The prevalence of dyslipidemia was 53.72%(7 450/13 869)for residents aged ≥22 years living in rural areas of Henan Province(59.32%(3 069/5 174)for men and 50.39%(4 381/8 695)for women). The adjusted prevalence of dyslipidemia was 50.50%(59.27% for men and 45.53% for women). The prevalence of hypercholesterolemia, hypertriglyceridemia, low HDL-C, and high LDL-C was 4.34%(602/13 868), 20.42%(2 826/13 837), 42.75%(5 927/13 865), and 3.14%(420/13 375), respectively, and the adjusted prevalence was 2.44%, 18.84%, 41.42%, and 1.86%, respectively. Logistic regression analyses showed that alcohol consumption(OR=1.27, 95% CI: 1.05-1.53), family history of hyperlipidemia(OR=1.29, 95% CI: 1.17-1.43), overweight(OR=1.40, 95% CI: 1.22-1.61), obesity(OR= 1.65, 95% CI: 1.39- 1.96), abnormal waist circumference(OR=1.22, 95% CI: 1.04- 1.43), and abnormal waist-height ratio(OR=1.21, 95% CI: 1.01-1.45)were significant independent risk factors, and high levels of physical activity(OR=0.85, 95% CI: 0.77- 0.95)and underweight(OR=0.52, 95% CI: 0.36- 0.75)were protective factors for dyslipidemia after adjusting for sex, age, education level, marital status, and income status. Conclusion: The prevalence of dyslipidemia was very high for this rural population. Alcohol consumption, family history of hyperlipidemia, overweight, obesity, abnormal waist circumference, and abnormal waist-height ratio were significant independent risk factors for dyslipidemia.

[Establishing a noninvasive prediction model for type 2 diabetes mellitus based on a rural Chinese population].

OBJECTIVE: To provide a noninvasive type 2 diabetes mellitus (T2DM) prediction model for a rural Chinese population. METHODS: From July to August, 2007 and July to August, 2008, a total of 20 194 participants aged ≥18 years were selected by cluster sampling technique from a rural population in two townships of Henan province, China. Data were collected by questionnaire interview, anthropometric measurement, and fasting plasma glucose and lipid profile examination. A total 17 265 participants were followed up from July to August, 2013 and July to October, 2014. Finally, 12 285 participants were selected for analysis. Data for these participants were randomly divided into a derivation group (derivation dataset, n= 6 143) and validation group (validation dataset, n=6 142) by 1∶1, respectively. Randomization was carried out by the use of computer-generated random numbers. A Cox regression model was used to analyze risk factors of T2DM in the derivation dataset. A T2DM prediction model was established by multiplying ß by 10 for each significant variable. After the total score was calculated by the model, analysis of the receiver operating characteristic (ROC) curve was performed. The area under the ROC curve (AUC) was used for evaluating model predictability. Furthermore, the model's predictability was validated in the validation dataset and compared with the Finnish Diabetes Risk Score (FINDRISC) model. RESULTS: A total 779 of 12 285 participants developed T2DM during the 6-year study period. The incidence rate was 6.12% in the derivation dataset (n=376) and 6.56% in the validation dataset (n=403). The difference was not statistically significant (χ(2)=1.00, P=0.316). A total of four noninvasive T2DM prediction models were established using the Cox regression model. The ROCs of the risk score calculated by the prediction models indicated that the AUCs of these models were similar (0.67-0.70). The AUC and Youden index of model 4 was the highest. The optimal cut-off value, sensitivity, specificity, and Youden index were scores of 25, 65.96%, 66.47%, and 0.32, respectively. Age, sleep time, BMI, waist circumference, and hypertension were selected as predictive variables. Using age<30 years as reference, ß values were 1.07, 1.58, and 1.67 and assigned scores were 11, 16, and 17 for age groups 30-44, 45-59, and ≥60 years, respectively. Using sleep time<8.0 h/d as reference, the ß value and assigned score were 0.27 and 3, respectively, for sleep time ≥10.0 h/d. Using BMI 18.5-23.9 kg/m(2) as reference, ß values were 0.53 and 1.00 and assigned scores 5 and 10, respectively, for BMI 24.0-27.9 kg/m(2), and ≥28.0 kg/m(2). Using waist circumference <85 cm for males/< 80 cm for females as reference, ß values were 0.44 and 0.65 and assigned scores 4 and 7, respectively, for 85 cm ≤ waist circumference <90 cm for males/80 cm≤ waist circumference <85 cm for females, and waist circumference ≥90 cm for males/≥85 cm for females. Using nonhypertension as reference, the respective ß value and assigned score were 0.34 and 3 for hypertension. The AUC performance of this model and the FINDRISC model was 0.66 and 0.64 (P=0.135), respectively, in the validation dataset. CONCLUSION: Based on this cohort study, a noninvasive prediction model that included age, sleep time, BMI, waist circumference, and hypertension was established, which is equivalent to the FINDRISC model and applicable to a rural Chinese population.

[Body mass index, waist circumference and waist-to-height ratio associated with the incidence of type 2 diabetes mellitus: a cohort study].

OBJECTIVE: To investigate the association between body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and the incidence risk of type 2 diabetes mellitus (T2DM). METHODS: In total, 20 194 participants ≥18 years old were selected randomly by cluster sampling from two township (town) of the county in Henan province from July to August of 2007 and July to August of 2008 and the investigation included questionnaires, anthropometric measurements, fasting plasma glucose, and lipid profile examination were performed at baseline; 17 236 participants were enrolled in this cohort study. 14 720 (85.4%) were followed up from July to August 2013 and July to October 2014. Finally, 11 643 participants (4 301 males and 7 342 females) were included in this study. Incidence density and Cox proportional hazards regression models were used to evaluate the risk of T2DM associated with baseline BMI, WC, WHtR, and their dynamic changes. RESULTS: After average of 6.01 years following up for 11 643 participants, 613 developed T2DM and the incidence density was 0.89 per 100 person-years. After adjusted for baseline sex, age, smoking, drinking, family history of diabetes, as well as the difference of fasting plasma-glucose (FPG), total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP) between baseline and follow-up, Cox Proportional-Hazards regression analysis indicated that T2DM risk of baseline BMI overweight group, BMI obesity group, abnormal WC group and abnormal WHtR group were significantly higher than that of the corresponding baseline normal groups , and the incidence risk of T2DM reached the highest for those whose baseline BMI, WC and WHtR were all abnormal, the corresponding HR (95%CI) were 2.05 (1.62-2.59), 3.01 (2.33-3.90), 2.34 (1.89-2.90), 2.88 (2.21-3.74), 3.32 (2.50-4.40), respectively. Whether baseline BMI/WC was normal or not, T2DM risk increased if baseline WHtR was abnormal, and the HR (95%CI) of baseline normal BMI/abnormal WHtR group, baseline abnormal BMI/abnormal WHtR group, baseline normal WC/abnormal WHtR group, baseline abnormal WC/abnormal WHtR group were 1.88 (1.29-2.74), 3.08 (2.34-4.05), 2.15(1.53-3.00), 3.22 (2.45-4.23), respectively. The analysis for dynamic changes of BMI, WC, and WHtR indicated that in baseline normal WC or WHtR group, T2DM risk increased when baseline normal WC or WHtR developed abnormal at follow-up, and the corresponding HR (95%CI) were 1.79 (1.26-2.55), 2.12(1.32-3.39), respectively. In baseline abnormal WC or WHtR group, T2DM risk decresed when baseline abnormal WC or WHtR reversed to normal at follow-up, and the corresponding HR (95%CI) were 2.16 (1.42-3.29), 2.62 (1.63-4.20), respectively. CONCLUSION: BMI, WC, and WHtR were associated with increased T2DM risk. The more abnormal aggregation of BMI, WC, and WHtR presents, the higher T2DM risk was. T2DM risk could be decreased when abnormal WC or WHtR reversed to normal.

PDK2 and ABCG2 genes polymorphisms are correlated with blood glucose levels and uric acid in Tibetan gout patients.

Previous studies have shown that the PDK2 and ABCG2 genes play important roles in many aspects of gout development in European populations. However, a detailed genotype-phenotype analysis was not performed. The aim of the present study was to investigate the potential association between variants in these two genes and metabolism-related quantitative phenotypes relevant to gout in a Chinese Tibetan population. In total, 316 Chinese Tibetan gout patients were recruited from rheumatology outpatient clinics and 6 single nucleotide polymorphisms in PDK2 and ABCG2 were genotyped, which were possible etiologic variants as identified in the HapMap Chinese Han Beijing population. A significant difference in blood glucose levels was detected between different genotypes of rs2728109 (P = 0.005) in the PDK2 gene. We also detected a significant difference in the mean serum uric levels between different genotypes of rs3114018 (P = 0.004) in the ABCG2 gene. All P values remained significant after Bonferroni's correction for multiple testing. Our data demonstrate potential roles for PDK2 and ABCG2 polymorphisms in the metabolic phenotypes of Tibetan gout patients, which may provide new insights into the etiology of gout. Further studies are required to confirm these findings.

Association between a functional genetic polymorphism (rs2230199) and age-related macular degeneration risk: a meta-analysis.

The association between the rs2230199 C>G single nucleotide polymorphism (SNP) in complement component 3 and age-related macular degeneration (AMD) risk has been examined extensively but the results are not consistent among studies. The aim of this study was to perform a meta-analysis of all available studies on this SNP in relation to AMD. The comprehensive databases of PubMed, Medline, Web of Knowledge, CNKI, and Google Scholar were searched for case-control studies investigating the association between the rs2230199 polymorphism and AMD susceptibility. ORs with 95%CIs were estimated to assess the association. Sensitivity analysis, test of heterogeneity, cumulative meta-analysis, and assessment of bias were also performed. A total of 15 published studies including 5593 cases and 5181 controls were used in this meta-analysis. Overall, the rs2230299 SNP was significantly associated with the risk of AMD in the overall population under the additive model (OR = 1.571, 95%CI = 1.414-1.745, P = 0.000), dominant model (OR = 1.681, 95%CI = 1.521-1.858, P = 0.000), and allelic model (OR = 1.597, 95%CI = 1.470-1.734, P = 0.000). In the subgroup analysis by ethnicity, the same results were found in Caucasian populations, while no significant correlations were found in Asian populations for all comparison models. In conclusion, our meta-analysis provides evidence that the rs2230199 polymorphism contributes to the development of AMD. Further large-scale multicenter epidemiological studies are warranted to confirm this finding.

Pulmonary selectivity and local pharmacokinetics of ambroxol hydrochloride dry powder inhalation in rat.

The aim of this study was to investigate the local pharmacokinetics and site-specific target efficiency of ambroxol hydrochloride (AH) dry powder inhalation (DPI) by comparing lung epithelial lining fluid (ELF) and plasma AH levels after tracheal administration (TA) with those after intravenous administration. Twelve rats were divided into two groups, one of which was given AH DPI (20 mg/kg) via the trachea and the other was given the same dose AH by intravenous injection (i.v.). Afterwards, each group was subdivided into two groups. The concentration of AH in the ELF was determined by microdialysis in one group while the concentration of AH in plasma was determined in the other group. After AH DPI (20 mg/kg) was given via the trachea, AH achieved a high local concentration in ELF and reached a C(max) at 1.5 h in plasma. After the same dose AH was given by i.v., AH reached a C(max) in ELF at 1.25 h. The (AUC(0-t))(ELF)/(AUC(0-t))(plasma) ratio (1.05-2.25) after TA differed significantly from the ratio (0.029-0.039) observed after intravenous administration (p < 0.05). All these results indicate that AH DPI can be delivered to a specific targeted site and achieve high target efficiency in ELF. DPI could be a useful drug delivery system for AH therapy of pulmonary diseases.

[The development of the multifunctional cephalostat and its applications in anesthesia].

The multifunctional cephalostat is able to hold the patients' head better and firmly at prone position after tracheal intubation under general anesthesia According to the size of patients head, the anesthetist can properly adjust the distance of the malor holder and the distance between the superciliary ridge and the lower jaw, and fix the two tempora to prevent the head swaying. So this instrument greatly facilitates the anesthesia managements.