Comparison of the Characteristics and Risk Factors of Carotid Atherosclerosis in High Stroke Risk Populations Between Urban and Rural Areas in North China

Zhang, Jin; Sang, Hui; Zhang, Xin; Fang, Yinchun; Niu, Xiaoyuan; T, Liu; Liu, Weidong; Li, Jian

doi:10.3389/fneur.2020.554778

Cited by 9 publications

(12 citation statements)

References 25 publications

(31 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our results showed that age, Sp, Dp, HCY level and HDL-C level were most important in all those four models, followed by gender, TC level and FPG level. Our findings were in consistent with previous studies, in which older age, gender, high Sp, hypertension, high TC level and high FPG levle were independently related to the risk of CAS 5 , 28 – 30 . High HCY level was also associated with the progression of CAS 31 .…”

Section: Discussionsupporting

confidence: 93%

“…High HCY level was also associated with the progression of CAS 31 . And high HDL-C level was a protective factor for CAS reported in a study with Chinese population 30 . Thus, models using decision tree, RF, XGBoost and SVM in our study suggested that age, Sp, Dp, HCY level, HDL-C level, gender, TC level and FPG level should be important in screening CAS in general and asymptomatic adults.…”

Section: Discussionmentioning

confidence: 79%

“…We acknowledged the limitation in our study that smoking history was not included in candidate features for developing models. It’s widely accepted that smoking is a risk factor for CAS 5 , 28 – 30 . However, no record of smoking history in our study.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Machine learning models for screening carotid atherosclerosis in asymptomatic adults

Zhou

Yang

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Carotid atherosclerosis (CAS) is a risk factor for cardiovascular and cerebrovascular events, but duplex ultrasonography isn’t recommended in routine screening for asymptomatic populations according to medical guidelines. We aim to develop machine learning models to screen CAS in asymptomatic adults. A total of 2732 asymptomatic subjects for routine physical examination in our hospital were included in the study. We developed machine learning models to classify subjects with or without CAS using decision tree, random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM) and multilayer perceptron (MLP) with 17 candidate features. The performance of models was assessed on the testing dataset. The model using MLP achieved the highest accuracy (0.748), positive predictive value (0.743), F1 score (0.742), area under receiver operating characteristic curve (AUC) (0.766) and Kappa score (0.445) among all classifiers. It’s followed by models using XGBoost and SVM. In conclusion, the model using MLP is the best one to screen CAS in asymptomatic adults based on the results from routine physical examination, followed by using XGBoost and SVM. Those models may provide an effective and applicable method for physician and primary care doctors to screen asymptomatic CAS without risk factors in general population, and improve risk predictions and preventions of cardiovascular and cerebrovascular events in asymptomatic adults.

show abstract

Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 79%

See 1 more Smart Citation

Machine learning models for screening carotid atherosclerosis in asymptomatic adults

Zhou

Yang

et al. 2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Early detection and management of hypertension may help slow the progression of CAS, and special attention should be given to subpopulations that are particularly vulnerable, such as men and smokers [43]. A high total cholesterol level was a risk factors for CAS in our study, which is similar to the findings of a previous study [44]. Elevated HDL-C levels were found to be an important protective factor, which coincides with a meta-analysis [45] and a cross-sectional study in urban populations in northern China [44].…”

Section: Discussionsupporting

confidence: 89%

The Impact of Dietary Diversity, Lifestyle, and Blood Lipids on Carotid Atherosclerosis: A Cross-Sectional Study

Wang

Liu

et al. 2022

Nutrients

View full text Add to dashboard Cite

Carotid atherosclerosis is a common arterial wall lesion that causes narrowing and occlusion of the arteries and is the basis of cardiovascular events. Dietary habits, lifestyle, and lipid metabolism should be considered integrally in the context of carotid atherosclerosis (CAS). However, this area has been investigated less often in China. To understand the prevalence of CAS in China and the impact of dietary diversity and habits, lifestyle, and lipid metabolism on CAS as well as its predictive factors, a cross-sectional study was performed in two northern and southern Chinese tertiary hospitals from 2017 to 2019. Included participants underwent carotid artery color Doppler ultrasonography, blood lipid examination and dietary evaluation. In total, 11,601 CAS patients and 27,041 individuals without carotid artery lesions were included. The prevalence of CAS was 30.0% in this group. High BMI (OR: 1.685, 95% CI [1.315–2.160]), current (1.148 [1.077–1.224]) or ex-smoking (1.349 [1.190–1.529]), abstinence from alcohol ((1.223 [1.026–1.459]), social engagement (1.122 [1.050–1.198]), hypertension (1.828 [1.718–1.945]), and total cholesterol (1.438 [1.298–1.594]) were risk factors for CAS, while higher dietary diversity according to DDS-2 (0.891 [0.805–0.989]), HDL-C (0.558 [0.487–0.639]), sugar-sweetened beverages (0.734 [0.696–0.774]), and no midnight snack consumption (0.846 [0.792–0.903]) were protective factors. This current study demonstrated that higher dietary diversity was a protective factor against CAS in a healthy population. In addition, current recommendations of healthy lifestyle and dietary habits for preventing CAS should be strengthened. In addition, dietary diversity should concentrate on food attributes and dietary balance, rather than increased quantities.

show abstract

“…Although urban males are well educated, have a higher income, and better access to medical facilities, they also have more unhealthy diets, more stressful daily activities, less physical exercise, longer sedentary time, and heavier air pollution than rural males [29][30][31]. Consistently, hypertension, carotid atherosclerosis, and overweight/obesity all showed a predisposition for urban residents and males in China [24,29,32]. Additionally, only urban males were predicted to not achieve the SDG target 3.4 for CRDs, primarily due to more air pollution and a higher prevalence of smoking, both of which are key risk factors for CRDs [33,34].…”

Section: Discussionmentioning

confidence: 98%

Current status of premature mortality from four non-communicable diseases and progress towards the Sustainable Development Goal target 3.4: a population-based study in northeast China, 2004–2017

Liu

Song

et al. 2021

BMC Public Health

View full text Add to dashboard Cite

Background and aim According to the United Nations’ Sustainable Development Goal (SDG) target 3.4, premature mortality from four non-communicable diseases (cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes mellitus, collectively referred to as NCD4) should achieve a minimum decline of 33% in 2030 relative to 2015. This remains a challenge for China. This study aimed to evaluate the current status and progress towards this target in Liaoning Province, one of the three provinces in northeast China. Methods We calculated the premature mortality rates (PMRs) per year and average annual percentage changes (AAPCs) from NCD4 using mortality data between 2004 and 2017. The trend was analyzed in the whole population, as well as in subpopulations of gender (male/female) and inhabiting area (urban/rural). PMRs from NCD4 for 2030 were projected by fitting a linear regression based on the current trend, which was identified by a Joinpoint model. Findings In the whole population, only chronic respiratory diseases showed a significant decline (AAPC: − 6.5%, p < 0.05), while only cancer showed a significant increase (AAPC: + 1.3%, p < 0.05); taken together, NCD4 showed a significant increase (AAPC: + 0.6%, p < 0.05). In the subpopulations, while males showed a significant increase in NCD4 (AAPC: + 1.5%, p < 0.05), cardiovascular diseases (AAPC: + 1.7%, p < 0.05), cancer (AAPC: + 1.8%, p < 0.05), and diabetes mellitus (AAPC: + 4.2%, p < 0.05), females showed a significant decline in NCD4 (AAPC: − 1.2%, p < 0.05), cardiovascular diseases (AAPC: − 1.8%, p < 0.05), diabetes mellitus (AAPC: − 2.1%, p < 0.05), but showed a mild increase in cancer (AAPC: + 0.5%, p > 0.05). A comparative analysis of the projected PMRs for 2030 with the 2015 levels revealed that only chronic respiratory diseases are expected to achieve the SDG target 3.4, apart from in the urban male subpopulation. Conclusion Except for chronic respiratory diseases, NCD4 cannot be expected to achieve the SDG target 3.4 in the whole population of Liaoning Province. Under these circumstances, special attention should be paid to reducing the risks of cancer and providing preventative interventions for men.

show abstract

Comparison of the Characteristics and Risk Factors of Carotid Atherosclerosis in High Stroke Risk Populations Between Urban and Rural Areas in North China

Cited by 9 publications

References 25 publications

Machine learning models for screening carotid atherosclerosis in asymptomatic adults

Machine learning models for screening carotid atherosclerosis in asymptomatic adults

The Impact of Dietary Diversity, Lifestyle, and Blood Lipids on Carotid Atherosclerosis: A Cross-Sectional Study

Current status of premature mortality from four non-communicable diseases and progress towards the Sustainable Development Goal target 3.4: a population-based study in northeast China, 2004–2017

Contact Info

Product

Resources

About