Metabolic syndrome in Xinjiang Kazakhs and construction of a risk prediction model for cardiovascular disease risk

Lei Mao, Jia He, Xiang Gao, Heng Guo, Kui Wang, Xianghui Zhang, Wenwen Yang, Jingyu Zhang, Shugang Li, Yunhua Hu, Lati Mu, Yizhong Yan, Jiaolong Ma, Yusong Ding, Mei Zhang, Jiaming Liu, Rulin Ma, Shuxia Guo

Research output: Contribution to journalArticle

Abstract

Background The high prevalence of metabolic syndrome (MetS) and cardiovascular diseases (CVD) is observed among Kazakhs in Xinjiang. Because MetS may significantly predict the occurrence of CVD, the inclusion of CVD-related indicators in metabolic network may improve the predictive ability for a CVD-risk model for Kazakhs in Xinjiang. Methods The study included 2,644 subjects who were followed for 5 years or longer. CVD cases were identified via medical records of the local hospitals from April 2016 to August 2017. Factor analysis was performed in 706 subjects (267 men and 439 women) with MetS to extract CVD-related potential factors from 18 biomarkers tested in a routine health check-up, served as a synthetic predictor (SP). We evaluated the predictive ability of the CVD-risk model using age and SP, logistic regression discrimination for internal validation (n = 384; men = 164, women = 220) and external validation (n = 219; men = 89, women = 130), calculated the probability of CVD for each participant, and receiver operating characteristic curves. Results According to the diagnostic criteria of JIS, the prevalence of MetS in Kazakh was 30.9%. Seven potential factors with a similar pattern were obtained from men and women and comprised the CVD predictors. When predicting CVD in the internal validation, the area under the curve (AUC) were 0.857 (95%CI 0.807–0.898) for men and 0.852 (95%CI 0.809–0.889) for women, respectively. In the external validation, the AUC to predict CVD were 0.914 (95%CI 0.832–0.963) for men and 0.848 (95%CI 0.774–0.905) for women. It is suggested that SP might serve as a useful tool in identifying CVD with in Kazakhs, especially for Kazakhs men. Conclusions Among 7 potential factors were extracted from 18 biomarkrs in Kazakhs with MetS, and SP may be used for CVD risk assessment.

Original languageEnglish (US)
Article numbere0202665
JournalPloS one
Volume13
Issue number9
DOIs
StatePublished - Sep 1 2018

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metabolic syndrome
cardiovascular diseases
Cardiovascular Diseases
prediction
China
Area Under Curve
Metabolic Diseases
Cytomegalovirus Infections
Biomarkers
Factor analysis
Metabolic Networks and Pathways
ROC Curve
Risk assessment
Statistical Factor Analysis
risk assessment
Medical Records
Logistics
biomarkers
Logistic Models
Health

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Mao, Lei ; He, Jia ; Gao, Xiang ; Guo, Heng ; Wang, Kui ; Zhang, Xianghui ; Yang, Wenwen ; Zhang, Jingyu ; Li, Shugang ; Hu, Yunhua ; Mu, Lati ; Yan, Yizhong ; Ma, Jiaolong ; Ding, Yusong ; Zhang, Mei ; Liu, Jiaming ; Ma, Rulin ; Guo, Shuxia. / Metabolic syndrome in Xinjiang Kazakhs and construction of a risk prediction model for cardiovascular disease risk. In: PloS one. 2018 ; Vol. 13, No. 9.
@article{6c6f363b1ed44076af046a828c8283e9,
title = "Metabolic syndrome in Xinjiang Kazakhs and construction of a risk prediction model for cardiovascular disease risk",
abstract = "Background The high prevalence of metabolic syndrome (MetS) and cardiovascular diseases (CVD) is observed among Kazakhs in Xinjiang. Because MetS may significantly predict the occurrence of CVD, the inclusion of CVD-related indicators in metabolic network may improve the predictive ability for a CVD-risk model for Kazakhs in Xinjiang. Methods The study included 2,644 subjects who were followed for 5 years or longer. CVD cases were identified via medical records of the local hospitals from April 2016 to August 2017. Factor analysis was performed in 706 subjects (267 men and 439 women) with MetS to extract CVD-related potential factors from 18 biomarkers tested in a routine health check-up, served as a synthetic predictor (SP). We evaluated the predictive ability of the CVD-risk model using age and SP, logistic regression discrimination for internal validation (n = 384; men = 164, women = 220) and external validation (n = 219; men = 89, women = 130), calculated the probability of CVD for each participant, and receiver operating characteristic curves. Results According to the diagnostic criteria of JIS, the prevalence of MetS in Kazakh was 30.9{\%}. Seven potential factors with a similar pattern were obtained from men and women and comprised the CVD predictors. When predicting CVD in the internal validation, the area under the curve (AUC) were 0.857 (95{\%}CI 0.807–0.898) for men and 0.852 (95{\%}CI 0.809–0.889) for women, respectively. In the external validation, the AUC to predict CVD were 0.914 (95{\%}CI 0.832–0.963) for men and 0.848 (95{\%}CI 0.774–0.905) for women. It is suggested that SP might serve as a useful tool in identifying CVD with in Kazakhs, especially for Kazakhs men. Conclusions Among 7 potential factors were extracted from 18 biomarkrs in Kazakhs with MetS, and SP may be used for CVD risk assessment.",
author = "Lei Mao and Jia He and Xiang Gao and Heng Guo and Kui Wang and Xianghui Zhang and Wenwen Yang and Jingyu Zhang and Shugang Li and Yunhua Hu and Lati Mu and Yizhong Yan and Jiaolong Ma and Yusong Ding and Mei Zhang and Jiaming Liu and Rulin Ma and Shuxia Guo",
year = "2018",
month = "9",
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Mao, L, He, J, Gao, X, Guo, H, Wang, K, Zhang, X, Yang, W, Zhang, J, Li, S, Hu, Y, Mu, L, Yan, Y, Ma, J, Ding, Y, Zhang, M, Liu, J, Ma, R & Guo, S 2018, 'Metabolic syndrome in Xinjiang Kazakhs and construction of a risk prediction model for cardiovascular disease risk', PloS one, vol. 13, no. 9, e0202665. https://doi.org/10.1371/journal.pone.0202665

Metabolic syndrome in Xinjiang Kazakhs and construction of a risk prediction model for cardiovascular disease risk. / Mao, Lei; He, Jia; Gao, Xiang; Guo, Heng; Wang, Kui; Zhang, Xianghui; Yang, Wenwen; Zhang, Jingyu; Li, Shugang; Hu, Yunhua; Mu, Lati; Yan, Yizhong; Ma, Jiaolong; Ding, Yusong; Zhang, Mei; Liu, Jiaming; Ma, Rulin; Guo, Shuxia.

In: PloS one, Vol. 13, No. 9, e0202665, 01.09.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Metabolic syndrome in Xinjiang Kazakhs and construction of a risk prediction model for cardiovascular disease risk

AU - Mao, Lei

AU - He, Jia

AU - Gao, Xiang

AU - Guo, Heng

AU - Wang, Kui

AU - Zhang, Xianghui

AU - Yang, Wenwen

AU - Zhang, Jingyu

AU - Li, Shugang

AU - Hu, Yunhua

AU - Mu, Lati

AU - Yan, Yizhong

AU - Ma, Jiaolong

AU - Ding, Yusong

AU - Zhang, Mei

AU - Liu, Jiaming

AU - Ma, Rulin

AU - Guo, Shuxia

PY - 2018/9/1

Y1 - 2018/9/1

N2 - Background The high prevalence of metabolic syndrome (MetS) and cardiovascular diseases (CVD) is observed among Kazakhs in Xinjiang. Because MetS may significantly predict the occurrence of CVD, the inclusion of CVD-related indicators in metabolic network may improve the predictive ability for a CVD-risk model for Kazakhs in Xinjiang. Methods The study included 2,644 subjects who were followed for 5 years or longer. CVD cases were identified via medical records of the local hospitals from April 2016 to August 2017. Factor analysis was performed in 706 subjects (267 men and 439 women) with MetS to extract CVD-related potential factors from 18 biomarkers tested in a routine health check-up, served as a synthetic predictor (SP). We evaluated the predictive ability of the CVD-risk model using age and SP, logistic regression discrimination for internal validation (n = 384; men = 164, women = 220) and external validation (n = 219; men = 89, women = 130), calculated the probability of CVD for each participant, and receiver operating characteristic curves. Results According to the diagnostic criteria of JIS, the prevalence of MetS in Kazakh was 30.9%. Seven potential factors with a similar pattern were obtained from men and women and comprised the CVD predictors. When predicting CVD in the internal validation, the area under the curve (AUC) were 0.857 (95%CI 0.807–0.898) for men and 0.852 (95%CI 0.809–0.889) for women, respectively. In the external validation, the AUC to predict CVD were 0.914 (95%CI 0.832–0.963) for men and 0.848 (95%CI 0.774–0.905) for women. It is suggested that SP might serve as a useful tool in identifying CVD with in Kazakhs, especially for Kazakhs men. Conclusions Among 7 potential factors were extracted from 18 biomarkrs in Kazakhs with MetS, and SP may be used for CVD risk assessment.

AB - Background The high prevalence of metabolic syndrome (MetS) and cardiovascular diseases (CVD) is observed among Kazakhs in Xinjiang. Because MetS may significantly predict the occurrence of CVD, the inclusion of CVD-related indicators in metabolic network may improve the predictive ability for a CVD-risk model for Kazakhs in Xinjiang. Methods The study included 2,644 subjects who were followed for 5 years or longer. CVD cases were identified via medical records of the local hospitals from April 2016 to August 2017. Factor analysis was performed in 706 subjects (267 men and 439 women) with MetS to extract CVD-related potential factors from 18 biomarkers tested in a routine health check-up, served as a synthetic predictor (SP). We evaluated the predictive ability of the CVD-risk model using age and SP, logistic regression discrimination for internal validation (n = 384; men = 164, women = 220) and external validation (n = 219; men = 89, women = 130), calculated the probability of CVD for each participant, and receiver operating characteristic curves. Results According to the diagnostic criteria of JIS, the prevalence of MetS in Kazakh was 30.9%. Seven potential factors with a similar pattern were obtained from men and women and comprised the CVD predictors. When predicting CVD in the internal validation, the area under the curve (AUC) were 0.857 (95%CI 0.807–0.898) for men and 0.852 (95%CI 0.809–0.889) for women, respectively. In the external validation, the AUC to predict CVD were 0.914 (95%CI 0.832–0.963) for men and 0.848 (95%CI 0.774–0.905) for women. It is suggested that SP might serve as a useful tool in identifying CVD with in Kazakhs, especially for Kazakhs men. Conclusions Among 7 potential factors were extracted from 18 biomarkrs in Kazakhs with MetS, and SP may be used for CVD risk assessment.

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U2 - 10.1371/journal.pone.0202665

DO - 10.1371/journal.pone.0202665

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AN - SCOPUS:85053158655

VL - 13

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 9

M1 - e0202665

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