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Hypertriglyceridemic-waist phenotype is strongly associated with cardiovascular risk factor clustering in Chinese adolescents. Sci Rep 2022; 12:15464. [PMID: 36104430 PMCID: PMC9474809 DOI: 10.1038/s41598-022-19690-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Accepted: 09/01/2022] [Indexed: 12/05/2022] Open
Abstract
The early identification of predictors related to cardiovascular risk factor clustering (CVRFC) in adolescents can help prevent Cardiovascular disease. The hypertriglyceridemic-waist circumference (HTW) phenotype is considered a simple and useful indicator to identify cardiovascular disease. However, there is limited research on the relationship between the HTW phenotype and (CVRFC) in adolescents. It is unclear whether the HTW phenotype can identify early the risk of developing CVRFC in adolescents. The study aimed to examine the association of the HTW phenotype with CVRFC in adolescents. A total of 1478 adolescents aged 12–18 years were classified into normal waist circumference (WC) and normal triglyceride (TG) (NWNT, 66.4%), normal WC and high TG (HTG, 5.5%), enlarged WC and normal TG (EW, 22.2%) and enlarged WC and high TG (HTW, 5.8%). High TG was defined as TG ≥ 1.47 mmol/L and enlarged WC ≥ 90th percentile by gender and age. CVRFs in this study included elevated blood pressure (BP), impaired fasting glucose (IFG), high total cholesterol (TC), low high-density lipoprotein cholesterol (HDL-C), and high low-density lipoprotein cholesterol (LDL-C). CVRFC ≥ 2 or CVRFC ≥ 3 were defined as the presence of at least two or three cardiovascular risk factors. After adjustment for BMI, gender and age, the HTW phenotype increased the risk of CVRFC ≥ 2 and CVRFC ≥ 3 compared to the NTNW phenotype, OR and 95%CI were 2.40 (1.23–4.58) and 3.63 (1.49–8.86), respectively. After stratification by gender, similar results were found in boys, however, girls with the EW phenotype had a lower risk of CVRFC ≥ 2 and CVRFC ≥ 3 compared with the NTNW phenotype after adjustment for BMI and age. The area under the ROC curve was 0.698 (0.661–0.736) and 0.782 (0.725–0.840) when TG was combined with WC to detect cardiovascular risk factors clustering, which was better than BMI, WHtR, TG or WC alone. And similar results were obtained for both boys and girls when stratified by gender. These results revealed that different combinations of TG and WC levels are closely associated with cardiovascular risk factors clustering in both boys and girls, and TG combining WC performed better than BMI, WHtR, TG or WC alone in detecting cardiovascular risk factor clustering in adolescents.
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Pan M, Gu J, Li R, Chen H, Liu X, Tu R, Chen R, Yu S, Mao Z, Huo W, Hou J, Wang C. Independent and combined associations of solid-fuel use and smoking with obesity among rural Chinese adults. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:10.1007/s11356-021-13081-8. [PMID: 33650053 DOI: 10.1007/s11356-021-13081-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 02/17/2021] [Indexed: 06/12/2023]
Abstract
Although solid-fuel use or smoking is associated with obesity measured by body mass index (BMI), research on their interactive effects on general and central obesity is limited. Data of 20,140 individuals in the Henan Rural Cohort Study was examined the independent and combined associations of solid-fuel use and smoking with prevalent obesity, which was measured by BMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). Multiple adjusted logistic regression models showed that the OR (95% CI) of prevalent obesity measured by BMI associated with exposure to solid fuels alone or with smoking was 0.78 (0.70, 0.86) or 0.46 (0.32, 0.66), compared with neither smoking nor solid-fuel exposure. Similar results had been found in other obese anthropometric indices and in the results of linear regression analysis. The results indicated that solid-fuel use and smoking have a synergistic effect on reduction in obesity indices. The effects of household air pollution from solid-fuel use and smoking on obesity should be considered when exploring the influencing factors of obesity.
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Affiliation(s)
- Mingming Pan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Jianjun Gu
- Department of Neurosurgery, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, People's Republic of China
| | - Ruiying Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Hao Chen
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Ruoling Chen
- Faculty of Education, Health and Wellbeing, University of Wolverhampton, Wolverhampton, UK
| | - Songcheng Yu
- Department of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
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Pan M, Tu R, Gu J, Li R, Liu X, Chen R, Yu S, Wang X, Mao Z, Huo W, Hou J, Wang C. Associations of Socioeconomic Status and Physical Activity With Obesity Measures in Rural Chinese Adults. Front Public Health 2021; 8:594874. [PMID: 33490019 PMCID: PMC7820760 DOI: 10.3389/fpubh.2020.594874] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 12/01/2020] [Indexed: 11/13/2022] Open
Abstract
Background: Although independent association of socioeconomic status (SES) or physical activity (PA) with obesity has been well-documented in urban settings, their independent and joint associations on obesity measures are limited in rural regions. Methods: Almost 38,000 (n = 37,922) individuals were included from the Henan Rural Cohort Study. The International Physical Activity Questionnaire (IPAQ) was used to evaluate PA. Obesity was reflected by body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). The independent and interactive effects of SES and PA on obesity were analyzed by logistic regression models and generalized linear regression models, respectively. Results: Compared with high education level, the OR (95%CI) of obesity defined by BMI with low education level was 1.466 (1.337, 1.608), 1.064 (0.924, 1.225), and 1.853 (1.625, 2.114) in total population, men and women, respectively. Besides, the OR (95%CI) of obesity defined by BMI associated with per capita monthly income were 1.089 (1.015, 1.170), 1.192 (1.055, 1.347), 1.038 (0.951, 1.133) in total population, men and women, respectively. Similar results had been observed in other obesity measures. Negative interactive association of low education level and PA on obesity measures were observed only in women (all P < 0.05). Conclusions: This study suggests that women are more susceptible to obesity concerning low SES and that adequate PA may be a potential target for mitigating the negative effect of low SES on obesity in women. Clinical Trial Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) http://www.chictr.org.cn/showproj.aspx?proj=11375.
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Affiliation(s)
- Mingming Pan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jianjun Gu
- Department of Neurosurgery, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, China
| | - Ruiying Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Ruoling Chen
- Faculty of Education, Health and Well-being, University of Wolverhampton, Wolverhampton, United Kingdom
| | - Songcheng Yu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zhenxing Mao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wenqian Huo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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Ma CM, Liu XL, Lu N, Wang R, Lu Q, Yin FZ. Hypertriglyceridemic waist phenotype and abnormal glucose metabolism: a system review and meta-analysis. Endocrine 2019; 64:469-485. [PMID: 31065910 DOI: 10.1007/s12020-019-01945-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Accepted: 04/29/2019] [Indexed: 01/18/2023]
Abstract
OBJECTIVE This study was to perform a meta-analysis to assess the relationship between hypertriglyceridemic-waist (HTW) phenotype and abnormal glucose metabolism. METHODS The data sources were PubMed and EMBASE up to June 2018. Studies providing the relationship between HTW phenotype and abnormal glucose metabolism were included. RESULTS In total, 48 eligible studies that evaluated 2,42,879 subjects were included in the meta-analysis. In the general population, the pooled odds ratios (ORs) for elevated blood glucose and diabetes related to HTW phenotype was 2.32 (95% confidence interval (CI): 1.98-2.71) and 2.69 (95% CI: 2.40-3.01), respectively. In cohort studies, the pooled OR for diabetes related to HTW phenotype was 2.89 (95% CI: 1.97-4.25) in subjects without diabetes. The levels of homeostasis model assessment of insulin resistance (HOMA-IR) in the HTW population were increased with values of mean differences (MD) 1.12 (95% CI: 0.81-1.43. P < 0.00001, I2 = 99%) in the general population and 0.89 (95% CI: 0.75-1.04, P < 0.00001, I2 = 67%) in subjects without diabetes. CONCLUSION HTW phenotype was closely associated with increased risk of abnormal glucose metabolism. There was also a significant correlation between HTW phenotype and insulin resistance.
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Affiliation(s)
- Chun-Ming Ma
- Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China
| | - Xiao-Li Liu
- Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China
| | - Na Lu
- Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China
| | - Rui Wang
- Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China
| | - Qiang Lu
- Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China
| | - Fu-Zai Yin
- Department of Endocrinology, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China.
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Kim SH, Abbasi F. Myths about Insulin Resistance: Tribute to Gerald Reaven. Endocrinol Metab (Seoul) 2019; 34:47-52. [PMID: 30912338 PMCID: PMC6435844 DOI: 10.3803/enm.2019.34.1.47] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 02/14/2019] [Accepted: 02/22/2019] [Indexed: 12/12/2022] Open
Abstract
Gerald Reaven was often called the "father of insulin resistance." On the 1-year anniversary of his death in 2018, we challenge three myths associated with insulin resistance: metformin improves insulin resistance; measurement of waist circumference predicts insulin resistance better than body mass index; and insulin resistance causes weight gain. In this review, we highlight Reaven's relevant research that helped to dispel these myths associated with insulin resistance.
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Affiliation(s)
- Sun H Kim
- Division of Endocrinology, Gerontology, and Metabolism, Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA.
| | - Fahim Abbasi
- Division of Cardiovascular Medicine, Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA
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