Advance Search
Turn off MathJax
Article Contents
WU Xun, QIN Yu, SU Jian, CHEN Lulu, CUI Lan, TAO Ran, ZHOU Jinyi. Associations of changes in waist circumference and BMI with variation of fasting blood glucose among middle aged and elderly at high cardio-vascular risk: a follow-up study in Jiangsu province[J]. Chinese Journal of Public Health. doi: 10.11847/zgggws1141575
Citation: WU Xun, QIN Yu, SU Jian, CHEN Lulu, CUI Lan, TAO Ran, ZHOU Jinyi. Associations of changes in waist circumference and BMI with variation of fasting blood glucose among middle aged and elderly at high cardio-vascular risk: a follow-up study in Jiangsu province[J]. Chinese Journal of Public Health. doi: 10.11847/zgggws1141575

Associations of changes in waist circumference and BMI with variation of fasting blood glucose among middle aged and elderly at high cardio-vascular risk: a follow-up study in Jiangsu province

doi: 10.11847/zgggws1141575
More Information
  • Corresponding author: QIN Yu,E-mail: qinyu@jscdc.cn
  • Received Date: 2023-02-24
  • Accepted Date: 2023-06-19
  • Rev Recd Date: 2023-04-19
  • Available Online: 2023-11-09
  •   Objective   To investigate associations of changes in waist circumference (WC) and body mass index (BMI) with the variation of fasting blood glucose among middle aged and elderly residents with high cardiovascular risk.   Methods  Totally 71 758 urban/rural permanent residents aged 35 years or older were recruited at 8 districts/counties of 3 municipalities, Jiangsu province for a baseline survey conducted during 2015 as a part of the ‘Early Screening and Comprehensive Intervention on Cardiovascular Diseases among High-Risk Populations in China’. Out of those residents surveyed, 12 369 individuals with initial records of fasting blood glucose (FBG) were identified as at high-risk of cardiovascular diseases and the individuals were groups were followed up annually in 2017, 2018, and 2019 to observe changes in their FBG levels over time. The generalized estimating equation (GEE) was used to explore associations of the changes in WC and BMI with the variations of FBG among the participants.   Results  Of the 9 952 participants at the baseline survey, 3 045 (30.6%), 2 130 (21.4%), and 4 777 (48.0%) had normal WC, pre-central obesity, and obesity and 56 (0.6%), 2 669 (26.8%), 4 540 (45.6%), and 2 687 (27.0%) were assessed as having underweight, normal weight, overweight, and obesity, respectively. After adjusting for gender, age, education, place of residence, smoking, alcohol drinking, hypertension, diabetes mellitus, dyslipidemia, baseline WC, baseline BMI, and follow-up sequence, the results of GEE analysis revealed that compared those the participants with normal WC, the participants having declined WC were at a decreased risk of abnormal FBG (odds ratio [OR] = 0.911, 95% confidence interval [95%CI]: 0.867 – 0.958) but the participants having elevated WC were at an increased risk of abnormal FBG (OR = 1.070, 95%CI: 1.022 – 1.120); the results also showed that every one centimeter increase in baseline WC and one unit increase in baseline BMI were associated with 0.011 mmol/L (β = 0.027, 95%CI: 0.013 – 0.041) and 0.027 mmol/L (β = 0.027, 95%CI: 0.013 – 0.041) increase in FBG. Further subgroup analysis demonstrated that every one centimeter increase in baseline WC was associated with 0.011/0.010, 0.014/0.005, and 0.007/0.021 mmol/L increase in FBG for the participants being male/female, living in urban/rural regions, and with/without diabetes (all P < 0.001); while, every one unit increase in baseline BMI was associated with 0.030, 0.026/0.024, and 0.031 mmol/L increase in FBG for the participants being female, living in urban/rural regions, and having diabetes, respectively (all P < 0.05).   Conclusion  There are positively linear associations of changes in WC and BMI with the variation of FBG among middle aged and elderly populations with high cardiovascular risk.
  • loading
  • [1]
    《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.
    [2]
    Jayedi A, Soltani S, Motlagh SZT, et al. Anthropometric and adiposity indicators and risk of type 2 diabetes: systematic review and dose-response meta-analysis of cohort studies[J]. BMJ, 2022, 376: e067516.
    [3]
    Fan YX, Wang RD, Ding L, et al. Waist circumference and its changes are more strongly associated with the risk of type 2 diabetes than body mass index and changes in body weight in Chinese adults[J]. The Journal of Nutrition, 2020, 150(5): 1259 – 1265. doi: 10.1093/jn/nxaa014
    [4]
    Fu WN, Wang C, Zou L, et al. Association of adiposity with diabetes: a national research among Chinese adults[J]. Diabetes/Metabolism Research and Reviews, 2021, 37(5): e3380.
    [5]
    Liu XC, Liu YS, Guan HX, et al. Comparison of six anthropometric measures in discriminating diabetes: a cross-sectional study from the national health and nutrition examination survey[J]. Journal of Diabetes, 2022, 14(7): 465 – 475. doi: 10.1111/1753-0407.13295
    [6]
    Yang QY, Liu YL, Jin ZF, et al. Evaluation of anthropometric indices as a predictor of diabetes in Dong and Miao ethnicities in China: a cross-sectional analysis of China Multi-Ethnic Cohort study[J]. PLoS One, 2022, 17(3): e0265228. doi: 10.1371/journal.pone.0265228
    [7]
    Jeon J, Jung KJ, Jee SH. Waist circumference trajectories and risk of type 2 diabetes mellitus in Korean population: the Korean genome and epidemiology study (KoGES)[J]. BMC Public Health, 2019, 19(1): 741. doi: 10.1186/s12889-019-7077-6
    [8]
    吴洵, 覃玉, 崔岚, 等. 江苏省居民心血管病高危人群流行病学特征及其影响因素分析[J]. 中华流行病学杂志, 2022, 43(1): 78 – 84. doi: 10.3760/cma.j.cn112338-20210201-00083
    [9]
    国家卫生健康委员会疾病预防控制局, 国家心血管病中心, 中国医学科学院阜外医院, 等. 中国高血压健康管理规范(2019)[J]. 中华心血管病杂志, 2020, 48(1): 10 – 46. doi: 10.3760/cma.j.issn.0253-3758.2020.01.004
    [10]
    中华医学会糖尿病学分会. 中国2型糖尿病防治指南(2020年版)[J]. 中华内分泌代谢杂志, 2021, 37(4): 311 – 398. doi: 10.3760/cma.j.cn311282-20210304-00142
    [11]
    中国成人血脂异常防治指南修订联合委员会. 中国成人血脂异常防治指南(2016年修订版)[J]. 中国循环杂志, 2016, 31(10): 937 – 950. doi: 10.3969/j.issn.1000-3614.2016.10.001
    [12]
    Haase CL, Lopes S, Olsen AH, et al. Weight loss and risk reduction of obesity-related outcomes in 0.5 million people: evidence from a UK primary care database[J]. International Journal of Obesity, 2021, 45(6): 1249 – 1258. doi: 10.1038/s41366-021-00788-4
    [13]
    Modi A, Gadhavi R, Pérez CM, et al. Longitudinal association between adiposity measures and regression of prediabetes/diabetes[J]. Nutrition, Metabolism, and Cardiovascular Diseases, 2021, 31(11): 3085 – 3094. doi: 10.1016/j.numecd.2021.07.005
    [14]
    Hu H, Kawasaki Y, Kuwahara K, et al. Trajectories of body mass index and waist circumference before the onset of diabetes among people with prediabetes[J]. Clinical Nutrition, 2020, 39(9): 2881 – 2888. doi: 10.1016/j.clnu.2019.12.023
    [15]
    Hou XH, Chen SY, Hu G, et al. Stronger associations of waist circumference and waist-to-height ratio with diabetes than BMI in Chinese adults[J]. Diabetes Research and Clinical Practice, 2019, 147: 9 – 18. doi: 10.1016/j.diabres.2018.07.029
    [16]
    German CA, Laughey B, Bertoni AG, et al. Associations between BMI, waist circumference, central obesity and outcomes in type II diabetes mellitus: The ACCORD Trial[J]. Journal of Diabetes and Its Complications, 2020, 34(3): 107499. doi: 10.1016/j.jdiacomp.2019.107499
    [17]
    Wang YL, Shirore RM, Ramakrishnan C, et al. Adiposity measures and pre-diabetes or diabetes in adults with hypertension in Singapore polyclinics[J]. The Journal of Clinical Hypertension, 2019, 21(7): 953 – 962. doi: 10.1111/jch.13587
    [18]
    Sekgala MD, Sewpaul R, Opperman M, et al. Comparison of the ability of anthropometric indices to predict the risk of diabetes mellitus in south African males: SANHANES-1[J]. International Journal of Environmental Research and Public Health, 2022, 19(6): 3224. doi: 10.3390/ijerph19063224
    [19]
    邓晓庆, 张梅, 张笑, 等. 中国成年人血糖水平现状及其与体质指数和腰围的关系[J]. 中华流行病学杂志, 2022, 43(8): 1178 – 1188. doi: 10.3760/cma.j.cn112338-20211011-00782
    [20]
    Bai KZ, Chen XJ, Song R, et al. Association of body mass index and waist circumference with type 2 diabetes mellitus in older adults: a cross-sectional study[J]. BMC Geriatrics, 2022, 22(1): 489. doi: 10.1186/s12877-022-03145-w
    [21]
    Ni XF, Jiao L, Zhang Y, et al. Correlation between the distribution of abdominal, pericardial and subcutaneous fat and muscle and age and gender in a middle-aged and elderly population[J]. Diabetes, Metabolic Syndrome and Obesity, 2021, 14: 2201 – 2208. doi: 10.2147/DMSO.S299171
    [22]
    Malone JI, Hansen BC. Does obesity cause type 2 diabetes mellitus (T2DM)? Or is it the opposite?[J]. Pediatric Diabetes, 2019, 20(1): 5 – 9. doi: 10.1111/pedi.12787
    [23]
    Wei JX, Liu X, Xue H, et al. Comparisons of visceral adiposity index, body shape index, body mass index and waist circumference and their associations with diabetes mellitus in adults[J]. Nutrients, 2019, 11(7): 1580. doi: 10.3390/nu11071580
    [24]
    高星星, 王丽敏, 张笑, 等. 2018年中国成年居民体重和腰围知晓状况及影响因素分析[J]. 中华流行病学杂志, 2022, 43(8): 1205 – 1214.
  • 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

    Tables(3)

    Article views (467) PDF downloads(147) Cited by()
    Proportional views
    Publishing history
    • Receive:  2023-02-24
    • Online:  2023-11-09

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return