Prevalence, awareness, treatment and control of hypertension in various ethnic groups (Hui, Kazakh, Kyrgyz, Mongolian, Tajik) in Xinjiang, Northwest China

Prevalence, awareness, treatment, control of hypertension among adults inhabited in the coastal area of Tianjin, China

Hypertension has long been a worldwide health concern. Our aim was to investigate the prevalence, awareness, treatment, and control rates of hypertension and analyze the factors related to hypertension among adult residents of the coastal areas of Tianjin, China. This was a cross-sectional study. Adults aged 35 to 75 years were selected for the study using cluster random sampling methods. Detailed information was collected via face-to-face surveys and medical checkups. We assessed the rates of hypertension in the total population and sub-populations and used multivariable logistic regression to identify the factors associated with the prevalence and the control of hypertension. In total, 6305 participants aged 55.22 ± 10.37 years were included in this study. Approximately 49.8% (95% confidence interval [CI]: 48.5%-51.1%) of the population had hypertension; the prevalence increased with age and body mass index (all P < .001). Multivariable logistic regression showed that the odds ratio of hypertension was 5.93 times more in participants aged 65 to 75 years than in those aged 35 to 44 (95% CI: 4.85-7.26, P < .001). The odds ratio of hypertension was 3.63 times more in obese participants than in those of normal weight (95% CI: 3.08-4.28, P < .001). Additionally, the awareness, treatment, control, and control under-treatment rates of hypertension were 89.7%, 83.6%, 54.4%, and 60.5%, respectively. Factors associated with having controlled hypertension included sex, body mass index, and dyslipidemia (all P < .01). Our study identified that in the coastal area of Tianjin, China, about half have hypertension, also the region has high rates of hypertension awareness, treatment and control, and more than half of hypertension patients receiving treatment have controlled hypertension.

Development and Validation of a Novel Nomogram to Predict the Impact of the Polymorphisms of the Variants of ICAM-1 Gene on the Prognosis of Ischemic Cardiomyopathy

Object

This study investigated the correlation between polymorphisms of the ICAM-1 gene and prognosis of Ischemic cardiomyopathy (ICM), and developed a prognostic model for predicting the prognosis ICM on the basis of ICAM-1 gene variants.

Methods

The current study included totally 576 patients with ICM. All patients are randomly divided into training group with 399 patients and validation group with 177 patients. The prognostic model was constructed by using the data of training group. Univariable Cox-regression analysis was performed, including clinical and gene variants, then used the least absolute shrinkage and selection operator (LASSO) regression model to optimize feature selection. Furthermore, multivariate Cox-regression was applied to build the prognostic nomogram model, which included clinical and gene features chosen by the LASSO regression model. Following that, the receiver operating characteristic (ROC) curve, C-index, calibration plot analyses and decision curve analysis (DCA) were carried out to evaluate the discrimination ability, consistency, and clinical utility of the prognostic model.

Results

Predicting factors rs281430, ventricular arrhythmia, treating by PCI or CABG, use of β-blockers, heart rate (HR), serum sodium level, left ventricular end-diastolic diameter (LVDD) were the risk factors of the prognosis of ICM, incorporated these factors into the prognostic nomogram model. The constructed nomogram performed well in discrimination ability, as observed by the ROC and C-index. Furthermore, as shown by calibration curves, our nomogram's predicted probabilities were highly consistent with measured values. With threshold probabilities, DCA suggested that our nomogram could be useful in the clinic.

Conclusion

rs281430 mutation (from AA genotype to AG or GG genotype) is a risk factor for ICM patients to have a higher survival probability; the survival probability of ICM patients with the mutant genotype (AG or GG) is lower than those with the wild genotype (AA).

Ethnicity Disparities in the Prevalence, Awareness, Treatment, and Control Rates of Hypertension in China

Objectives

Previous studies reported that there were disparities in hypertension management among different ethnic groups, and this study aimed to systematically determine the prevalence, awareness, treatment, and control rates of hypertension in multiple Chinese ethnic groups.

Methods

We searched Embase, PubMed, and Web of Science for articles up to 25 October, 2022. The pooled prevalence, awareness, treatment, and control rates of hypertension were estimated with 95% confidence intervals (CI). The heterogeneity of estimates among studies was assessed by the Cochran Q test and I ² statistic. Meta-regression analyses were conducted to identify the factors influencing the heterogeneity of the pooled prevalence, awareness, treatment, and control rate of hypertension.

Results

In total, 45 publications including 193,788 cases and 587,826 subjects were eligible for the analyses. The lowest prevalence was found in the Han group (27.0%), and the highest prevalence was in the Mongolian population (39.8%). The awareness rates ranged from 24.4% to 58.0% in the four ethnic groups. Both the highest treatment and control rates were found in the Mongolian population (50.6% and 16.0%, respectively), whereas the Yi group had the lowest control rate (8.0%). In addition, the study year, the mean age of subjects, mean body mass index of subjects, tobacco use (%), alcohol use (%), residence (urban%), and education (primary school%) had varied effects on heterogeneity.

Conclusions

These findings highlight the disparities in prevalence, awareness, treatment, and control rates of hypertension in a different ethnic population of China, which could provide suggestions for making targeted prevention measures.

Development and validation of a predictive model of the impact of single nucleotide polymorphisms in the ICAM-1 gene on the risk of ischemic cardiomyopathy

OBJECTIVE

Previous research has linked single nucleotide polymorphisms (SNPs) in the ICAM-1 gene to an increased risk of developing ischemic cardiomyopathy (ICM); however, a diagnostic model of ICM according to the ICAM-1 variant has not yet been developed. Therefore, this study aimed to explore the correlation between SNPs in ICAM-1 and the presence of ICM, along with developing a diagnostic model for ICM based on the variants of the ICAM-1 gene.

METHOD

This study recruited a total of 252 patients with ICM and 280 healthy controls. In addition, all the participants were genotyped for SNPs in the ICAM-1 gene by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Using the training dataset of 371 people, we constructed a nomogram model based on ICAM-1 gene variants and clinical variables. To optimize the feature choice for the ICM risk model, a least absolute shrinkage and selection operator (LASSO) regression model was adopted. We also employed multivariable logistic regression analysis to build a prediction model by integrating the clinical characteristics chosen in the LASSO regression model. Following the receiver operating characteristic (ROC), a calibration plot and decision curve analysis (DCA) were used to evaluate the discrimination, calibration, and clinical usefulness of the predictive model.

RESULT

The predictors involved in the prediction nomogram included age, smoking, diabetes, low-density lipoprotein-cholesterol, hemoglobin, N-terminal pro-B-type natriuretic peptide, ejection fraction, and the rs5491 SNP. The nomogram model exhibited good discrimination ability, with the AUC value of ROC of 0.978 (95%CI: 0.967-0.989, P < 0.001) in the training group and 0.983 (95% CI: 0.969-0.998, P < 0.001) in the validation group. The Hosmer-Lemeshow test demonstrated good model calibration with consistency (P training group = 0.937; P validation group = 0.910). The DCA showed that the ICM nomogram was clinically beneficial, with the threshold probabilities ranging from 0.0 to 1.0.

CONCLUSION

The AT genotype in rs5491 of the ICAM-1 gene was associated with having a higher frequency of ICM. Individuals carrying the mutant AT genotype showed a 5.816-fold higher frequency of ICM compared with those with the AA genotype. ICM patients with the AT genotype also had a higher rate of cardiogenic death. We, therefore, developed a nomogram model that could offer an individualized prediction of ICM risk factors.

Development and validation of prediction models for hypertension risks: A cross-sectional study based on 4,287,407 participants

Objective

To develop an optimal screening model to identify the individuals with a high risk of hypertension in China by comparing tree-based machine learning models, such as classification and regression tree, random forest, adaboost with a decision tree, extreme gradient boosting decision tree, and other machine learning models like an artificial neural network, naive Bayes, and traditional logistic regression models.

Methods

A total of 4,287,407 adults participating in the national physical examination were included in the study. Features were selected using the least absolute shrinkage and selection operator regression. The Borderline synthetic minority over-sampling technique was used for data balance. Non-laboratory and semi-laboratory analyses were carried out in combination with the selected features. The tree-based machine learning models, other machine learning models, and traditional logistic regression models were constructed to identify individuals with hypertension, respectively. Top features selected using the best algorithm and the corresponding variable importance score were visualized.

Results

A total of 24 variables were finally included for analyses after the least absolute shrinkage and selection operator regression model. The sample size of hypertensive patients in the training set was expanded from 689,025 to 2,312,160 using the borderline synthetic minority over-sampling technique algorithm. The extreme gradient boosting decision tree algorithm showed the best results (area under the receiver operating characteristic curve of non-laboratory: 0.893 and area under the receiver operating characteristic curve of semi-laboratory: 0.894). This study found that age, systolic blood pressure, waist circumference, diastolic blood pressure, albumin, drinking frequency, electrocardiogram, ethnicity (uyghur, hui, and other), body mass index, sex (female), exercise frequency, diabetes mellitus, and total bilirubin are important factors reflecting hypertension. Besides, some algorithms included in the semi-laboratory analyses showed less improvement in the predictive performance compared to the non-laboratory analyses.

Conclusion

Using multiple methods, a more significant prediction model can be built, which discovers risk factors and provides new insights into the prediction and prevention of hypertension.

lncNALT knockdown ameliorates hypertensive retinopathy via PTEN/PI3K/AKT pathway

This study aimed to explore the role of the long non-coding RNA NOTCH1-associated lncRNA in T cell acute lymphoblastic leukemia (lncNALT) in the pathogenesis of hypertensive retinopathy (HR). LncNALT expression levels were determined using reverse transcription-quantitative polymerase chain reaction. The effects of lncNALT knockdown on the viability, proliferation, migration, and invasion of human retinal microvascular endothelial cells (RMECs) were determined via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide, 5-ethynyl-2'-deoxyuridine staining, and Transwell assays. Protein expression levels were determined using western blotting. We found that lncNALT expression levels were increased in RMECs treated with hydrogen peroxide (H₂O₂), while the knockdown of lncNALT rescued the viability, proliferation, migration, and invasion of RMECs treated with H₂O₂. Moreover, lncNALT interacted with ELAV like RNA binding protein 1 to affect the phosphatase and tensin homolog (PTEN) expression. Knockdown of lncNALT enhanced the viability, proliferation, migration, and invasion of RMECs via the PTEN/phosphoinositide 3-kinase (PI3K)/serine-threonine kinase (AKT) pathway. Taken together, knockdown of lncNALT enhanced the viability, proliferation, migration, and invasion of RMECs via the PTEN/PI3K/AKT pathway, suggesting that lncNALT could be a potential therapeutic target for patients with HR.

Association between ethnicity and health knowledge among the floating population in China

Background

Health equity remains a priority concerns by central government in China. This study aimed to explore ethnic gaps in access to health knowledge categories and sources based on the survey data from a publicly available dataset.

Methods

Data were from 2015 China Migrants Dynamic Survey issued by The National Health Commission in China. Descriptive analyses were performed to reflect geodemographic differences in the floating population of ethnic minority (EMFP) and Han majority (HMFP) with Chi-square test. Ethnic gaps in access to health knowledge categories and sources were explored with Poisson regressions, logistic regressions, and bivariate ordered probit regressions.

Results

In the sample, most of participants had inadequate health information literacy. There were significant differences regarding geodemographic factors between EMFP and HMFP. Illiterate EMFP had likelihood to obtain less health knowledge categories (IRR = 0.80, 95% CI 0.77–0.84) and sources (IRR = 0.83, 95% CI 0.80–0.86) as compared to illiterate HMFP. Most of correlations between health knowledge categories and sources were weak in the samples of EMFP and HMFP.

Conclusion

Ethnic disparities in access to health knowledge categories and sources among the floating population in China were confirmed. Further effective efforts should be provided to reduce ethnic disparities in access to health knowledge under the ethnicity-orientated support of public health resource.

Development and Validation of a Prediction Model for 5-Year Risk of Kidney Dysfunction in Patients with Hypertension and Glucose Metabolism Disorder

Purpose

Patients with hypertension and glucose metabolism disorder (GMD) are at high risk of developing kidney dysfunction (KD). Therefore, we aimed to develop a nomogram for predicting individuals’ 5-year risk of KD in hypertensives with GMD.

Patients and Methods

In total, 1961 hypertensives with GMD were consecutively included. Baseline data were extracted from medical electronic system, and follow-up data were obtained using annual health check-ups or hospital readmission. KD was defined as estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m². Subjects were randomly divided into training and validation sets with a ratio of 7 to 3. Least absolute shrinkage and selection operator method was used to identify potential predictors. Cox proportional hazard model was applied to build a nomogram for predicting KD risk. The discriminative ability, calibration and usefulness of the model were evaluated. The prediction model was verified by internal validation.

Results

During the follow-up of 5351 person-years with a median follow-up of 32 (range: 3–91) months, 130 patients developed KD. Age, sex, ethnicity, hemoglobin A1c, uric acid, and baseline eGFR were identified as significant predictors for incident KD and used for establishing nomogram. The prediction model displayed good discrimination with C-index of 0.770 (95% CI: 0.712–0.828) and 0.763 (95% CI: 0.704–0.823) in training and validation sets, respectively. Calibration curve indicated good agreement between the predicted and actual probabilities. The decision curve analysis demonstrated that the model was clinically useful.

Conclusion

The prediction nomogram, including six common easy-to-obtain factors, shows good performance for predicting 5-year risk of KD in hypertensives with GMD. This quantitative tool could help clinicians, and even primary care providers, recognize potential KD patients early and make strategy for prevention and management.

Genetic Variation of Migration Inhibitory Factor Gene rs2070766 Is Associated With Acute Coronary Syndromes in Chinese Population

Genetic variation of macrophage migration inhibitory factor (MIF) gene has been linked to coronary artery disease. We investigated an association between the polymorphism of MIF gene rs2070766 and acute coronary syndromes (ACS) and the predictive value of MIF gene variation in clinical outcomes. This study involved in 963 ACS patients and 932 control subjects from a Chinese population. All participants were genotyped for the single nucleotide polymorphism (SNP) of MIF gene rs2070766 using SNPscan™. A nomogram model using MIF genetic variation and clinical variables was established to predict risk of ACS. Major adverse cardiovascular events (MACE) were monitored during a follow-up period. The frequency of rs2070766 GG genotype was higher in ACS patients than in control subjects (6.2 vs 3.8%, p = 0.034). Multivariate logistic regression analysis revealed that individuals with mutant GG genotype had a 1.7-fold higher risk of ACS compared with individuals with CC or CG genotypes. Using MIF rs2070766 genotypes and clinical factors, we developed a nomogram model to predict risk of ACS. The nomogram model had a good discrimination with an area under the curve of 0.781 (95% CI: 0.759-0.804), concordance index of 0.784 (95% CI: 0.762-0.806) and well-fitted calibration. During the follow-up period of 25 months, Kaplan-Meier curves demonstrated that ACS patients carrying GG phenotype developed more MACE compared to CC or CG carriers (p < 0.05). GG genotype of MIF gene rs2070766 was associated with a higher risk of ACS in a Chinese population. The GG genotype carriers in ACS patients had worse clinical outcomes compared with those carrying CC or CG genotype. Together with rs2070766 genetic variant of MIF gene, we established a novel nomogram model that can provide individualized prediction for ACS.

The Genetic Structure and East-West Population Admixture in Northwest China Inferred From Genome-Wide Array Genotyping

Northwest China is a contacting region for East and West Eurasia and an important center for investigating the migration and admixture history of human populations. However, the comprehensive genetic structure and admixture history of the Altaic speaking populations and Hui group in Northwest China were still not fully characterized due to insufficient sampling and the lack of genome-wide data. Thus, We genotyped genome-wide SNPs for 140 individuals from five Chinese Mongolic, Turkic speaking groups including Dongxiang, Bonan, Yugur, and Salar, as well as the Hui group. Analysis based on allele-sharing and haplotype-sharing were used to elucidate the population history of Northwest Chinese populations, including PCA, ADMIXTURE, pairwise Fst genetic distance, f-statistics, qpWave/qpAdm and ALDER, fineSTRUCTURE and GLOBETROTTER. We observed Dongxiang, Bonan, Yugur, Salar, and Hui people were admixed populations deriving ancestry from both East and West Eurasians, with the proportions of West Eurasian related contributions ranging from 9 to 15%. The genetic admixture was probably driven by male-biased migration- showing a higher frequency of West Eurasian related Y chromosomal lineages than that of mtDNA detected in Northwest China. ALDER-based admixture and haplotype-based GLOBETROTTER showed this observed West Eurasian admixture signal was introduced into East Eurasia approximately 700 ∼1,000 years ago. Generally, our findings provided supporting evidence that the flourish transcontinental communication between East and West Eurasia played a vital role in the genetic formation of northwest Chinese populations.

Effects of Simplified Antihypertensive Treatment Algorithm on Hypertension Management and Hypertension-Related Death in Resource-Constricted Primary Care Setting between 1997 and 2017

Hypertension management is poor in primary care settings of developing countries, where 75% of hypertensives are living. Exploring better ways to improve hypertension management and to decrease stroke and CVD death is needed such as introducing treatment algorithm. Therefore, we selected intervention counties from Xinjiang, an underdeveloped region in China, and introduced antihypertensive treatment algorithm, comprising locally available and affordable agents, to primary health providers since 1998. Program effects were evaluated using the data collected in various ways including cross-sectional screenings to population ≥30 years between 1998 and 2015 by comparing treatment and control rates of hypertension, changes in blood pressure (BP) levels and distribution, and proportion of case/total and NCD death for CVD and stroke. Compared to 1998-2000, treatment rate was improved by 2.78 fold (11.2% vs. 32.1%, P < 0.001), and the overall and treated control rate were improved by 53.5 fold (0.2% vs. 10.7%, P < 0.001) and by 16.8 fold (2.0% vs. 33.5%, P < 0.001), respectively, in 2015. Mean SBP and DBP showed a net reduction by 33.7 mmHg (181.3 vs. 147.6 mmHg) and 21.3 mmHg (106.3 vs. 85.0 mmHg), respectively, in 2015, compared to 1998-2000 (P < 0.001), and stage III hypertension was reduced by 75.2% (33.5 vs. 8.3%, P < 0.001). Compared to 1997-1999, stroke/NCD death was reduced by 34.1% in 2015-2017 (31.7 vs. 20.9%, P = 0.006) in the intervention counties whereas by 7.5% in control county. Introduction of treatment algorithm helps improve hypertension management and reduce stroke death in resource-constricted primary settings.

Development and validation of a nomogram to better predict hypertension based on a 10-year retrospective cohort study in China

Background

Hypertension is a highly prevalent disorder. A nomogram to estimate the risk of hypertension in Chinese individuals is not available.

Methods

6201 subjects were enrolled in the study and randomly divided into training set and validation set at a ratio of 2:1. The LASSO regression technique was used to select the optimal predictive features, and multivariate logistic regression to construct the nomograms. The performance of the nomograms was assessed and validated by AUC, C-index, calibration curves, DCA, clinical impact curves, NRI, and IDI.

Results

The nomogram^140/90 was developed with the parameters of family history of hypertension, age, SBP, DBP, BMI, MCHC, MPV, TBIL, and TG. AUCs of nomogram^140/90 were 0.750 in the training set and 0.772 in the validation set. C-index of nomogram^140/90 were 0.750 in the training set and 0.772 in the validation set. The nomogram^130/80 was developed with the parameters of family history of hypertension, age, SBP, DBP, RDWSD, and TBIL. AUCs of nomogram^130/80 were 0.705 in the training set and 0.697 in the validation set. C-index of nomogram^130/80 were 0.705 in the training set and 0.697 in the validation set. Both nomograms demonstrated favorable clinical consistency. NRI and IDI showed that the nomogram^140/90 exhibited superior performance than the nomogram^130/80. Therefore, the web-based calculator of nomogram^140/90 was built online.

Conclusions

We have constructed a nomogram that can be effectively used in the preliminary and in-depth risk prediction of hypertension in a Chinese population based on a 10-year retrospective cohort study.

Funding

This study was supported by the Hebei Science and Technology Department Program (no. H2018206110).