YAN HUA WU

Dr. YAN HUA WU


Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 March 2017 in Lipids in Health and Disease
Verified
Journal Article
Open access
PDF file
FZFu-Liang Zhang
Fu-Liang Zhang
YXYingqi Xing
Yingqi Xing
YWYAN HUA WU
YAN HUA WU
HLHao-Yuan Liu
Hao-Yuan Liu
YLYun Luo
Yun Luo
YYYi Yang
Yi Yang
Dyslipidemia is an important independent modifiable risk factor for cardiovascular disease. The aim of this study was to explore the current prevalence, awareness, treatment and control of dyslipidemia and its associated influence factors in northeast China. In this population-based cross-sectional study, we adopted a multi-stage, stratified sampling method to obtain a representative sample of 4052 permanent residents aged 40 years and over from different urban and rural regions in Dehui City of Jilin Province. All subjects completed a questionnaire and were examined for risk factors. Continuous data were presented as means ± standard deviations (SD) and compared using the Student’s t-test. Categorical variables were presented as proportions and compared using the Rao-Scott-χ 2 test in different subgroups. The associated influence factors for the prevalence, awareness, treatment and control of dyslipidemia were evaluated through multivariate logistic regression. The prevalence of dyslipidemia was 62.1% overall, with 33.5, 43.9, 0.6, and 8.8% for high total cholesterol, triglyceride, low-density lipoprotein cholesterol, and low high-density lipoprotein cholesterol, respectively. Among those with dyslipidemia, the proportion of subjects who were aware, treated, and controlled was 14.4, 33.9, and 19.9%, respectively. Overweight or obesity (OR = 2.156; 95% CI: 1.863, 2.533), hypertension (OR = 1.643; 95% CI: 1.425, 1.893), or diabetes mellitus (OR = 2.173; 95% CI: 1.661, 2.844) increased the prevalence of dyslipidemia, also these participants were more likely to be aware of their condition, however, this did not increase the likelihood of treatment and control. Living in urban areas and higher education level also increased the awareness of dyslipidemia. Personal history of coronary heart disease was the strongest influence factors associated with better awareness, treatment and control of dyslipidemia. Overweight or obesity (OR = 0.404; 95% CI: 0.235, 0.695) and lack of exercise (OR = 0.423; 95% CI: 0.215, 0.830) were associated with poor control of dyslipidemia. The prevalence of dyslipidemia among adults aged 40 years and over in northeast China was high, however, the awareness, treatment, and control of dyslipidemia was measured at far from desirable levels. Renewed efforts taking influence factors into account are needed to improve the current unsatisfactory condition.

1 November 2015 in Public Health
Verified
Journal Article
Closed access
SWShibin Wang
Shibin Wang
CDC. D'ARcy
C. D'ARcy
YYY.Q. Yu
Y.Q. Yu
BLBo Li
Bo Li
YLYawen Liu
Yawen Liu
CKChanggui Kou
Changgui Kou

28 June 2017 in Lipids in Health and Disease
Verified
Journal Article
Open access
PDF file
LZLili Zhang
Lili Zhang
YYYueyue You
Yueyue You
YWYAN HUA WU
YAN HUA WU
YZYangyu Zhang
Yangyu Zhang
MWMohan Wang
Mohan Wang
CKChanggui Kou
Changgui Kou
BUD13 homolog (BUD13), one of submits of the retention and splicing complex, was identified in yeast as a splicing factor that affected nuclear pre-mRNA retention. While more and more studies demonstrated that BUD13 played a potential role in the pathogenesis of metabolic syndrome (MetS). This objective was to reassess whether novel locus of BUD13 were linked to MetS and individual complements in the northeast of China. A total of 3850 individuals were recruited in this case-control study, including 1813 MetS cases and 2037 healthy controls. The diagnostic criteria was according to the International Diabetes Federation (IDF). Metabolic complements such as waist circumference (WC), triglyceride, high-density lipoprotein cholesterol (HDL-C), systolic and diastolic blood pressure (SBP and DBP), and fasting glucose were measured. We explored the association between two novel single nucleotide polymorphism (SNPs) of BUD13 (rs7118999 and rs10488698) and MetS and its complements. Using binary logistic regression analysis we found that there were no significant associations between SNPs and MetS in different heritance models (all P > 0.05). However, novel locus of BUD13 were linked to individual complements in MetS cases. Rs7118999 conferred to risk of WC (P = 0.016) and the carrier of TT might have higher susceptibility to MetS. While rs10488698 was associated with HDL-C (P = 0.001) and the carrier of TT was significantly associated with higher level of HDL-C. We concluded that novel mutations in BUD13 did not confer risk for MetS in our study population, but these mutations changed the level of metabolic complements.