scholarly journals AGE- AND GENDER-SPECIFIC ASSOCIATION BETWEEN METABOLIC SYNDROME COMPONENTS AND SUBCLINICAL ARTERIAL STIFFNESS IN A CHINESE POPULATION

Heart ◽  
2012 ◽  
Vol 98 (Suppl 2) ◽  
pp. E153.2-E153
Author(s):  
Chunyan Weng ◽  
Hong Yuan
Keyword(s):  
Metabolic Syndrome ◽  
Arterial Stiffness ◽  
Chinese Population ◽  
Age And Gender ◽  
Specific Association ◽  
And Gender ◽  
Gender Specific ◽  
Metabolic Syndrome Components

scholarly journals Age- and Gender Dependent Association between Components of Metabolic Syndrome and Subclinical Arterial Stiffness in a Chinese Population

2012 ◽  
Vol 9 (8) ◽  
pp. 730-737 ◽  
Author(s):  
Chunyan Weng ◽  
Hong Yuan ◽  
Xiaohong Tang ◽  
Zhijun Huang ◽  
Kan Yang ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Arterial Stiffness ◽  
Chinese Population ◽  
Age And Gender ◽  
And Gender

scholarly journals Gender-specific association of metabolic syndrome and its components with arterial stiffness in the general Chinese population

PLoS ONE ◽  
2017 ◽  
Vol 12 (10) ◽  
pp. e0186863 ◽  
Author(s):  
Mengjia Yue ◽  
Hongjian Liu ◽  
Minfu He ◽  
Fangyuan Wu ◽  
Xuanxuan Li ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Arterial Stiffness ◽  
Chinese Population ◽  
Specific Association ◽  
Gender Specific ◽  
General Chinese Population

scholarly journals Age and gender specific association between obesity and depressive symptoms: a large-scale cross-sectional study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wei Liao ◽  
Zhicheng Luo ◽  
Yitan Hou ◽  
Ningning Cui ◽  
Xiaotian Liu ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Cohort Study ◽  
Depressive Symptoms ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Age And Gender ◽  
Specific Association ◽  
And Gender ◽  
Gender Specific

Abstract Background This is a cross-sectional study to explore the age and gender specific association between obesity and depression in Chinese rural adults. Methods A total of 29,900 eligible participants from the Henan Rural Cohort Study were included. Standard anthropometric measurements were undertaken to obtain data on body mass index (BMI) and waist circumference (WC). The Patient Health Questionnaire-2 (PHQ-2) was utilized to discover depressive symptoms. Logistic regression was performed to explore the association between obesity (independent variable) and depressive symptoms (dependent variable). Results There were 1777 subjects with depressive symptoms, accounting for 5.94%. After multivariable adjustment, compared with normal weight group, the odds ratios (ORs) [95% confidence interval (CI)] for depressive symptoms in underweight, overweight and general obese groups were 1.41 (1.08–1.84), 0.87 (0.78–0.97) and 0.86 (0.74–0.99), respectively. Similarly, the OR (95% CI) of abdominal obesity group was 0.84 (0.76–0.93). Besides, there was linear decreasing trend of WC with depressive symptoms, but not BMI. Moreover, the inverse association between obesity and depressive symptoms was stronger in men and the elderly than that in women and the young. Conclusion Underweight was associated with a higher prevalence of depressive symptoms, which indicated that health care should pay attention to underweight as well as obesity, especially for women and the young. Clinical trial registration The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 2015-07-06.

scholarly journals Mining Cancer-Specific Disease Comorbidities from a Large Observational Health Database

2014 ◽  
Vol 13s1 ◽  
pp. CIN.S13893 ◽  
Author(s):  
Yang Chen ◽  
Rong Xu
Keyword(s):  
Metabolic Syndrome ◽  
Adverse Event Reporting System ◽  
Adverse Event Reporting ◽  
Age And Gender ◽  
Genetic Mechanisms ◽  
Patient Groups ◽  
The Common ◽  
Health Database ◽  
And Gender ◽  
Metabolic Syndrome Components

Cancer comorbidities often reflect the complex pathogenesis of cancers and provide valuable clues to discover the underlying genetic mechanisms of cancers. In this study, we systematically mine and analyze cancer-specific comorbidity from the FDA Adverse Event Reporting System. We stratified 3,354,043 patients based on age and gender, and developed a network-based approach to extract comorbidity patterns from each patient group. We compared the comorbidity patterns among different patient groups and investigated the effect of age and gender on cancer comorbidity patterns. The results demonstrated that the comorbidity relationships between cancers and non-cancer diseases largely depend on age and gender. A few exceptions are depression, anxiety, and metabolic syndrome, whose comorbidity relationships with cancers are relatively stable among all patients. Literature evidences demonstrate that these stable cancer comorbidities reflect the pathogenesis of cancers. We applied our comorbidity mining approach on colorectal cancer and detected its comorbid associations with metabolic syndrome components, diabetes, and osteoporosis. Our results not only confirmed known cancer comorbidities but also generated novel hypotheses, which can illuminate the common pathophysiology between cancers and their co-occurring diseases.

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