Advance Search
Volume 39 Issue 11
Nov.  2023
Turn off MathJax
Article Contents
FENG Xiaoyan, WANG Junyi, WU Shan, WANG Zhihao, LI Lürong, HUANG Jilong, CHEN Qingsong, SHEN Tianran. Associations of abdominal obesity indexes with hypertension in elderly physical examinees in Zhongshan city: a cross-sectional analysis[J]. Chinese Journal of Public Health, 2023, 39(11): 1397-1406. doi: 10.11847/zgggws1140468
Citation: FENG Xiaoyan, WANG Junyi, WU Shan, WANG Zhihao, LI Lürong, HUANG Jilong, CHEN Qingsong, SHEN Tianran. Associations of abdominal obesity indexes with hypertension in elderly physical examinees in Zhongshan city: a cross-sectional analysis[J]. Chinese Journal of Public Health, 2023, 39(11): 1397-1406. doi: 10.11847/zgggws1140468

Associations of abdominal obesity indexes with hypertension in elderly physical examinees in Zhongshan city: a cross-sectional analysis

doi: 10.11847/zgggws1140468
More Information
  • Corresponding author: SHEN Tianran, E-mail: shentrgz@163.com
  • Received Date: 2023-02-28
  • Accepted Date: 2023-10-13
  • Rev Recd Date: 2023-08-14
  • Available Online: 2023-11-28
  • Publish Date: 2023-11-01
  •   Objective  To explore the relationship between abdominal obesity index and hypertension among the elderly in Zhongshan city for the prevention and control of hypertension.   Methods  The data of the analysis were from 8 318 residents aged ≥ 65 years and participating in free physical examination project during June – September 2020 in a town and a district of Zhongshan city, Guangdong province. Multivariate logistic regression model was used to analyze the relationship between abdominal obesity indexes and hypertension among the residents; the abdominal obesity indexes included neck circumference (NC), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), lipid accumulation product (LAP), and China visceral obesity index (CVAI). The dose-response correlation between NC and the risk of hypertension was analyzed with restricted cubic splines.   Results  The observed prevalence rate of hypertension among the elderly physical examinees was 45.5% (44.4% in the males and 46.3% in the females). Compared to those in the male and female non-hypertensives, significantly higher mean values of NC (37.29 ± 2.83 cm vs. 36.41 ± 2.82 cm and 33.91 ± 2.67 cm vs. 33.04 ± 2.55 cm), WC (87.90 ± 9.51 cm vs. 84.40 ± 9.59 cm and 86.52 ± 9.48 cm vs. 83.24 ± 9.50 cm), WHR (0.93 ± 0.07 vs. 91 ± 0.07 and 0.91 ± 0.07 vs. 0.90 ± 0.07), WHtR (0.54 ± 0.06 vs. 0.52 ± 0.06 and 0.57 ± 0.06 vs. 0.55 ± 0.06), LAP (43.00 ± 38.70 vs. 32.54 ± 31.22 and 46.98 ± 39.47 vs. 58.08 ± 46.96), and CVAI (116.19 ± 42.01 vs. 98.42 ± 42.94 and 133.18 ± 30.78 vs. 119.80 ± 30.25) were measured in the hypertensives (all P < 0.001). After adjusting for age, education, marital status, monthly household income per capita, smoking, alcohol drinking, exercise, salted vegetable consumption habits, body mass index (BMI), fasting blood glucose (FPG), total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C) and high density lipoprotein cholesterol (HDL-C), multivariate logistic regression analysis showed that the risk of hypertension increased in the male elderly with higher NC compared to that in those with the NC of the lowest quartile (third quartile: odds ratio [OR] = 1.314, 95% confidence interval [CI]: 1.029 – 1.676; the highest quartile: OR = 1.512, 95%CI: 1.131 – 2.022) and in the female elderly with higher WHtR compared to that in those with the WHtR of the lowest quartile (second quartile: OR = 1.214, 95%CI: 1.009 – 1.463; third quartile: OR = 1.289, 95%CI: 1.084 – 1.532; the highest quartile: OR = 1.503, 95%CI: 1.223 – 1.846); the analysis also demonstrated that the risk of hypertension decreased in the male elderly with higher WHtR (the second quartile vs. the lowest quartile: OR = 0.636, 95%CI: 0.469 – 0.863). After adjusting for confounding factors mentioned above, the results of restricted cubic spline analysis revealed a linear dose-response relationship between NC and hypertension risk in both the male and the female elderly (χ2 = 94.62 and 128.22, both P < 0.001).   Conclusion  There is a positive linear correlation between NC and the risk of hypertension among the elderly in Zhongshan City.
  • loading
  • [1]
    Natsis M, Antza C, Doundoulakis I, et al. Hypertension in obesity: novel insights[J]. Current Hypertension Reviews, 2020, 16(1): 30 – 36.
    [2]
    Di Palo KE, Barone NJ. Hypertension and heart failure: prevention, targets, and treatment[J]. Heart Failure Clinics, 2020, 16(1): 99 – 106. doi: 10.1016/j.hfc.2019.09.001
    [3]
    王增武, 李苏宁. 老年高血压患病率一路“走高”[J]. 养生大世界, 2019(12): 34 – 36.
    [4]
    Lüscher TF. Novel insights into body fat distribution and cardiometabolic risk[J]. European Heart Journal, 2019, 40(34): 2833 – 2836. doi: 10.1093/eurheartj/ehz634
    [5]
    Koenen M, Hill MA, Cohen P, et al. Obesity, adipose tissue and vascular dysfunction[J]. Circulation Research, 2021, 128(7): 951 – 968. doi: 10.1161/CIRCRESAHA.121.318093
    [6]
    王亮亮, 黄瑜, 郭伟, 等. 肥胖和中心性肥胖对高血压的交互作用分析[J]. 预防医学, 2022, 34(2): 129 – 134. doi: 10.19485/j.cnki.issn2096-5087.2022.02.005
    [7]
    Khanna D, Peltzer C, Kahar P, et al. Body mass index (BMI): a screening tool analysis[J]. Cureus, 2022, 14(2): e22119.
    [8]
    Korhonen PE, Mikkola T, Kautiainen H, et al. Both lean and fat body mass associate with blood pressure[J]. European Journal of Internal Medicine, 2021, 91: 40 – 44. doi: 10.1016/j.ejim.2021.04.025
    [9]
    Nazare JA, Smith J, Borel AL, et al. Usefulness of measuring both body mass index and waist circumference for the estimation of visceral adiposity and related cardiometabolic risk profile (from the INSPIRE ME IAA study)[J]. The American Journal of Cardiology, 2015, 115(3): 307 – 315. doi: 10.1016/j.amjcard.2014.10.039
    [10]
    Xia MF, Lin HD, Chen LY, et al. Association of visceral adiposity and its longitudinal increase with the risk of diabetes in Chinese adults: a prospective cohort study[J]. Diabetes/Metabolism Research and Reviews, 2018, 34(7): e3048. doi: 10.1002/dmrr.3048
    [11]
    Garvey WT, Mechanick JI, Brett EM, et al. American association of clinical endocrinologists and American College of Endocrin-ology comprehensive clinical practice guidelines for medical care of patients with obesity[J]. Endocrine Practice, 2016, 22 Suppl 3: 1 – 203.
    [12]
    Omura-Ohata Y, Son C, Makino H, et al. Efficacy of visceral fat estimation by dual bioelectrical impedance analysis in detecting cardiovascular risk factors in patients with type 2 diabetes[J]. Cardiovascular Diabetology, 2019, 18(1): 137. doi: 10.1186/s12933-019-0941-y
    [13]
    Zhao L, Huang GL, Xia FZ, et al. Neck circumference as an independent indicator of visceral obesity in a Chinese population[J]. Lipids in Health and Disease, 2018, 17(1): 85. doi: 10.1186/s12944-018-0739-z
    [14]
    Varghese M, Song JR, Singer K. Age and Sex: impact on adipose tissue metabolism and inflammation[J]. Mechanisms of Ageing and Development, 2021, 199: 111563. doi: 10.1016/j.mad.2021.111563
    [15]
    del Moral-Trinidad LE, Romo-González T, Carmona Figueroa YP, et al. Potential for body mass index as a tool to estimate body fat in young people[J]. Enfermería Clínica (English Edition), 2021, 31(2): 99 – 106.
    [16]
    Streng KW, Voors AA, Hillege HL, et al. Waist-to-hip ratio and mortality in heart failure[J]. European Journal of Heart Failure, 2018, 20(9): 1269 – 1277. doi: 10.1002/ejhf.1244
    [17]
    Peer N, Lombard C, Steyn K, et al. Waist-to-height ratio is a useful indicator of cardio-metabolic risk in South Africa[J]. Family Practice, 2020, 37(1): 36 – 42.
    [18]
    Ahn N, Baumeister SE, Amann U, et al. Visceral adiposity index (VAI), lipid accumulation product (LAP), and product of triglycerides and glucose (TyG) to discriminate prediabetes and diabetes[J]. Scientific Reports, 2019, 9(1): 9693. doi: 10.1038/s41598-019-46187-8
    [19]
    Qiao TT, Luo T, Pei HL, et al. Association between abdominal obesity indices and risk of cardiovascular events in Chinese populations with type 2 diabetes: a prospective cohort study[J]. Cardiovascular Diabetology, 2022, 21(1): 225. doi: 10.1186/s12933-022-01670-x
    [20]
    中华医学会健康管理学分会, 中华健康管理学杂志编委会. 健康体检基本项目专家共识[J]. 中华健康管理学杂志, 2014, 8(2): 81 – 90. doi: 10.3760/cma.j.issn.1674-0815.2014.02.004
    [21]
    郑新, 井丽, 刘文利, 等. 2018年辽宁省农村 ≥ 40岁居民肥胖患病率及其相关影响因素分析[J]. 中国公共卫生, 2020, 36(12): 1817 – 1821.
    [22]
    Feng XY, Wang JY, Wang SP, et al. Correlation analysis of anthropometric indices and type 2 diabetes mellitus in residents aged 60 years and older[J]. Frontiers in Public Health, 2023, 11: 1122509. doi: 10.3389/fpubh.2023.1122509
    [23]
    李楠, 李智文, 李舜, 等. 中国山西省部分农村妇女食用腌制咸菜与高血压的关联研究[J]. 中国生育健康杂志, 2017, 28(3): 201 – 204, 211.
    [24]
    《中国成人超重和肥胖预防控制指南》修订委员会. 中国成人超重和肥胖预防控制指南(2021)[M]. 北京: 人民卫生出版社, 2021.
    [25]
    《中国高血压防治指南》修订委员会. 中国高血压防治指南(2018年修订版)[M]. 北京: 人民卫生出版社, 2018.
    [26]
    Wang ZW, Chen Z, Zhang LF, et al. Status of hypertension in China: results from the China hypertension survey, 2012 – 2015[J]. Circulation, 2018, 137(22): 2344 – 2356. doi: 10.1161/CIRCULATIONAHA.117.032380
    [27]
    Commodore-Mensah Y, Samuel LJ, Dennison-Himmelfarb CR, et al. Hypertension and overweight/obesity in Ghanaians and Nigerians living in West Africa and industrialized countries: a systematic review[J]. Journal of Hypertension, 2014, 32(3): 464 – 472. doi: 10.1097/HJH.0000000000000061
    [28]
    Mozafar Saadati H, Sabour S, Mansournia MA, et al. Effect modification of general and central obesity by sex and age on cardiovascular outcomes: targeted maximum likelihood estimation in the atherosclerosis risk in communities study[J]. Diabetes and Metabolic Syndrome:Clinical Research and Reviews, 2021, 15(2): 479 – 485. doi: 10.1016/j.dsx.2021.02.024
    [29]
    吴永君, 张维森, 周柏靖, 等. 自然绝经年龄与绝经后肥胖关系[J]. 中国公共卫生, 2022, 38(12): 1544 – 1548. doi: 10.11847/zgggws1138576
    [30]
    陈冯梅, 郭志荣, 海波, 等. 体质指数、腰围、腰臀比和腰高比对高血压发病影响前瞻性队列研究[J]. 中国公共卫生, 2021, 37(12): 1774 – 1777.
    [31]
    Sardinha LB, Santos DA, Silva AM, et al. A comparison between BMI, waist circumference, and waist-to-height ratio for identifying cardio-metabolic risk in children and adolescents[J]. PLoS One, 2016, 11(2): e0149351. doi: 10.1371/journal.pone.0149351
    [32]
    Momin M, Fan FF, Li JP, et al. Joint effects of body mass index and waist circumference on the incidence of hypertension in a community-based Chinese population[J]. Obesity Facts, 2020, 13(2): 245 – 255. doi: 10.1159/000506689
    [33]
    Hingorjo MR, Zehra S, Imran E, et al. Neck circumference: a supplemental tool for the diagnosis of metabolic syndrome[J]. JPMA. The Journal of the Pakistan Medical Association, 2016, 66(10): 1221 – 1226.
    [34]
    Kroll C, Mastroeni SSBS, Czarnobay SA, et al. The accuracy of neck circumference for assessing overweight and obesity: a systematic review and meta-analysis[J]. Annals of Human Biology, 2017, 44(8): 667 – 677. doi: 10.1080/03014460.2017.1390153
    [35]
    Saneei P, Shahdadian F, Moradi S, et al. Neck circumference in relation to glycemic parameters: a systematic review and meta-analysis of observational studies[J]. Diabetology and Metabolic Syndrome, 2019, 11(1): 50. doi: 10.1186/s13098-019-0445-7
    [36]
    Alzeidan R, Fayed A, Hersi AS, et al. Performance of neck circumference to predict obesity and metabolic syndrome among adult Saudis: a cross-sectional study[J]. BMC Obesity, 2019, 6(1): 13. doi: 10.1186/s40608-019-0235-7
    [37]
    Assyov Y, Gateva A, Tsakova A, et al. A comparison of the clinical usefulness of neck circumference and waist circumference in individuals with severe obesity[J]. Endocrine Research, 2017, 42(1): 6 – 14. doi: 10.3109/07435800.2016.1155598
    [38]
    Preis SR, Massaro JM, Hoffmann U, et al. Neck circumference as a novel measure of cardiometabolic risk: the Framingham Heart study[J]. The Journal of Clinical Endocrinology and Metabolism, 2010, 95(8): 3701 – 3710. doi: 10.1210/jc.2009-1779
    [39]
    Namazi N, Larijani B, Surkan PJ, et al. The association of neck circumference with risk of metabolic syndrome and its components in adults: a systematic review and meta-analysis[J]. Nutrition, Metabolism and Cardiovascular Diseases, 2018, 28(7): 657 – 674. doi: 10.1016/j.numecd.2018.03.006
    [40]
    Singh R, Barrios A, Dirakvand G, et al. Human brown adipose tissue and metabolic health: potential for therapeutic avenues[J]. Cells, 2021, 10(11): 3030. doi: 10.3390/cells10113030
    [41]
    张成龙. 血浆游离脂肪酸、β2微球蛋白水平与冠心病患者冠脉病变严重程度的相关性分析[D]. 长沙: 中南大学, 2014.
    [42]
    Aoi S, Miyake T, Harada T, et al. Neck circumference has possibility as a predictor for metabolic syndrome in postmeno-pausal women[J]. Hiroshima Journal of Medical Sciences, 2014, 63(4): 27 – 32.
    [43]
    Henderson GC. Plasma free fatty acid concentration as a modifiable risk factor for metabolic disease[J]. Nutrients, 2021, 13(8): 2590. doi: 10.3390/nu13082590
    [44]
    Shi J, Wang ZX, Zhang WW, et al. Neck circumference as an independent predictor for NAFLD among postmenopausal women with normal body mass index[J]. Nutrition and Metabolism, 2021, 18(1): 30. doi: 10.1186/s12986-021-00562-3
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(1)  / Tables(6)

    Article views (157) PDF downloads(25) Cited by()
    Proportional views
    Publishing history
    • Receive:  2023-02-28
    • Online:  2023-11-28
    • Published:  2023-11-01

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return