Metabolic syndrome in hypertensive adults from rural Northeast China
An update
Bibliographic Data
| ID | 15375874 |
|---|---|
| Authors | Shasha Yu (0000-0001-5336-4519, China Medical University, corresponding author), Xiaofan Guo (0000-0002-7220-5094, First Hospital of China Medical University), Hongmei Yang (0000-0002-9048-2546, First Hospital of China Medical University), Liqiang Zheng (0000-0003-0101-9398, China Medical University), Yingxian Sun (0000-0001-9701-8984, China Medical University) |
| Year | 2015 |
| Volume | 15 |
| Issue | 1 |
| Pages | 247-247 |
| Publication date | 2015-03-13 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1471-2458 • E-ISSN: 1471-2458 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s12889-015-1587-7 |
| PMID | 25880417 |
| PMCID | PMC4367840 |
| OpenAlex | W2059835889 |
| Language | EN |
| Citations received | 4 |
| References cited | 28 |
The prevalence of MetS was dramatically high and exhibited a remarkably increasing trend in hypertensive rural Northeast Chinese. Female had higher incidence of MetS while male had more drastically increasing trend
Abdominal obesity · Biostatistics · Cholesterol · Confounding · Diabetes mellitus · Environmental health · Hypertriglyceridemia · Incidence (geometry · Logistic regression · Metabolic syndrome · Obesity · Triglyceride · Chronic Disease Management Strategies · Demography · Diabetes Management and Education · Diabetes, Cardiovascular Risks, and Lipoproteins · Medicine · Endocrinology · Epidemiology · Internal Medicine
Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China
Building capacity for a disability-inclusive response to violence against women and girls
Prevalence of Diabetes and Impaired Fasting Glucose in Hypertensive Adults in Rural China
Freedom to go where I want
| Unique citing works | 4 |
|---|---|
| Citations per year | 0,36 |
| Citation span | 2015 - 2025 (11) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 4 |