Correlation of Serum Uric Acid Level and Body Fat Distribution in Individuals by Glucose Metabolism

doi:10.12114/j.issn.1007-9572.2021.00.507

Abstract

Abstract: Background　Hyperuricemia is an important manifestation of metabolic diseases，and a significant risk factor for type 2 diabetes and obesity and so on.However，there are few studies on the correlation between serum uric acid level and body fat distribution in individuals by glucose metabolism.Objective　To investigate the relationship between serum uric acid level and body fat distribution in adult population by glucose metabolism.Methods　A total of 571 adult permanent residents were recruited from Shanghai Nicheng Town Yunsong Community in 2015.According to the 1998 WHO diagnostic criteria for diabetes，they were divided into groups of normal glucose tolerance （NGT），impaired glucose regulation （IGR），and type 2 diabetes mellitus（T2DM）.Hyperuricemia was diagnosed according to the 2010 Chinese Expert Consensus Recommendations for the Diagnosis and Treatment of Asymptomatic Hyperuricemia with Cardiovascular Diseases.Intragroup comparisons of the general demographic information，biochemical and body fat indices by hyperuricemia prevalence were performed to examine the potential association of serum uric acid level and body fat indices.Results　The hypeluricemia prevalence was 12.2%（24/196），21.8%（27/170），and 14.6%（30/205），respectively，in NGT，IGR and T2DM groups，showing no significant statistical difference（χ2=1.042，P=0.594）.In NGT group，those with hyperuricemia had greater mean age，and greater average levels of BMI，triacylglycerol，fasting insulin，trunk fat percentage to leg fat percentage （TFP/LFP） ratio，trunk fat mass to limb fat mass（TFM/LFM） ratio，abdominal fat percentage to hip fat percentage （AFP/HFP） ratio，and lower average level of high-density lipoprotein cholesterol （HDL-C） than those without（P<0.05）.In IGR group，those with hyperuricemia had higher men ratio，waist-to-hip ratio，TFP/LFP ratio，TFM/LFM ratio，and AFP/HFP ratio，and lower average levels of HDL-C，upper and lower limb fat percentages than those without （P<0.05）.In T2DM group，Those with hyperuricemia had greater average age and women ratio，and higher average levels of BMI，total cholesterol，low-density lipoprotein cholesterol，body fat percentage，trunk fat percentage，upper limb fat percentage，and lower limb fat percentage than those without （P<0.05）.Pearson correlation analysis results showed that the level of serum uric acid was positively correlated with TFP/LFP ratio，TFM/LFM ratio and AFP/HFP ratio （P<0.05）in each group；serum uric acid level was positively correlated with waist-to-hip ratio，but negatively correlated with body fat percentage，trunk fat percentage，upper limb fat percentage，and lower limb fat percentage in NGT and IGR groups（P<0.05）.Conclusion　The serum uric acid level and body fat distribution differed significantly among individuals by glucose metabolism，and the serum uric acid level may be closely related to body fat distribution.

Key words: Glucose metabolism disorders；Diabetes mellitus；Uric acid；Body fat distribution；Factor analysis, statistical

摘要： 背景　作为代谢性疾病的重要表现之一，高尿酸血症是2型糖尿病、肥胖症等疾病的重要危险因素，但是目前关于不同糖代谢水平人群血尿酸水平与体脂分布的相关性研究甚少。目的　探究不同糖代谢人群血尿酸水平与体脂分布的相关性。方法　2015年选取上海市泥城镇云松社区常住居民571例为研究对象。根据世界卫生组织（WHO）1998年制定的糖尿病诊断标准，将受试者分为糖耐量正常组（NGT组）、糖耐量异常组（IGR组）、2型糖尿病组（T2DM组）。根据2010年《无症状高尿酸血症合并心血管疾病诊治建议中国专家共识》诊断高尿酸血症。比较NGT组、IGR组、T2DM组不同血尿酸水平者一般资料、生化指标和体脂指标，并分析不同糖代谢水平者血尿酸水平与各体脂指标的相关性。结果　NGT组196例，其中高尿酸血症24例（12.2%）；IGR组170例，其中高尿酸血症27例（21.8%）；T2DM组205例，其中高尿酸血症30例（14.6%）。三组高尿酸血症发生率比较，差异无统计学意义（χ2=1.042，P=0.594）。NGT组无高尿酸血症者年龄小于高尿酸血症者，体质指数（BMI）、三酰甘油（TG）、空腹胰岛素、躯干脂肪百分比/腿部脂肪百分比（TF%/LF%）、躯干脂肪质量/四肢脂肪质量（TFM/LFM）、腹臀比（A/G）低于高尿酸血症者，高密度脂蛋白胆固醇（HDL-C）高于高尿酸血症者（P<0.05）。IGR组无高尿酸血症者男性所占比例、腰臀比、TF%/LF%、TFM/LFM、A/G低于高尿酸血症者，HDL-C、上肢脂肪百分比（ULF%）、下肢脂肪百分比（LLF%）高于高尿酸血症者（P<0.05）。T2DM组无高尿酸血症者年龄小低于高尿酸血症者，女性所占比例、BMI、总胆固醇（TC）、低密度脂蛋白胆固醇（LDL-C）、全身脂肪百分比（BF%）、躯干脂肪百分比（TF%）、ULF%、LLF%低于高尿酸血症者（P<0.05）。Pearson相关分析结果显示，不同糖代谢水平者血尿酸水平与TF%/LF%、TFM/LFM、A/G均呈正相关（P<0.05）；NGT组、IGR组血尿酸水平与腰臀比呈正相关，与BF%、TF%、ULF%、LLF%呈负相关（P<0.05）。结论　不同糖代谢水平人群血尿酸水平、体脂分布均存在差异，且血尿酸水平与体脂分布情况密切相关。

关键词: 葡萄糖代谢障碍；糖尿病；尿酸；体脂分布；因素分析, 统计学

XIAO Yuanyuan,JIANG Zhifeng,JIANG Fusong, et al. Correlation of Serum Uric Acid Level and Body Fat Distribution in Individuals by Glucose Metabolism　[J]. Chinese General Practice, 2021, 24(21): 2675-2679. DOI: 10.12114/j.issn.1007-9572.2021.00.507.
肖元元,姜智峰,蒋伏松等. 不同糖代谢水平人群血尿酸水平与体脂分布的相关性分析[J]. 中国全科医学, 2021, 24(21): 2675-2679. DOI: 10.12114/j.issn.1007-9572.2021.00.507.

References

［1］ZHANG S，WANG Y，CHENG J，et al．Hyperuricemia and cardiovascular disease［J］．Curr Pharm Des，2019，25（6）：700-709．DOI：10.2174/1381612825666190408122557.
［2］YAMADA A，SATO K K，KINUHATA S，et al．Association of visceral fat and liver fat with hyperuricemia［J］．Arthritis Care Res：Hoboken，2016，68（4）：553-561．DOI：10.1002/acr.22729.
［3］ALBERTI K G，ZIMMET P Z.Definition，diagnosis and classification of diabetes mellitus and its complications.Part 1：diagnosis and classification of diabetes mellitus provisional report of a WHO consultation［J］．Diabet Med，1998，15（7）：539-553．DOI：10.1002/（SICI）1096-9136（199807）15：7<539：：AID-DIA668>3.0.CO；2-S.
［4］中国医师协会心血管内科医师分会，中国医师协会循证医学专业委员会.无症状高尿酸血症合并心血管疾病诊治建议中国专家共识［J］．中国综合临床，2010，26（7）：780-784．DOI：10.3760/cma.j.issn.1008-6315.2010.07.042.
［5］CHEN M Y，ZHAO C C，LI T T，et al．Serum uric acid levels are associated with obesity but not cardio-cerebrovascular events in Chinese inpatients with type 2 diabetes［J］．Sci Rep，2017，7：40009．DOI：10.1038/srep40009.
［6］SHARAF EL DIN U A A，SALEM M M，ABDULAZIM D O.Uric acid in the pathogenesis of metabolic，renal，and cardiovascular diseases：a review［J］．J Adv Res，2017，8（5）：537-548．DOI：10.1016/j.jare.2016.11.004.
［7］COOK D G，SHAPER A G，THELLE D S，et al．Serum uric acid，serum glucose and diabetes：relationships in a population study［J］．Postgrad Med J，1986，62（733）：1001-1006．DOI：10.1136/pgmj.62.733.1001.
［8］YUAN H J，YANG X G，SHI X Y，et al．Association of serum uric acid with different levels of glucose and related factors［J］．Chin Med J （Engl），2011，124（10）：1443-1448.
［9］BOCK G，DALLA MAN C，CAMPIONI M，et al．Pathogenesis of pre-diabetes：mechanisms of fasting and postprandial hyperglycemia in people with impaired fasting glucose and/or impaired glucose tolerance［J］．Diabetes，2006，55（12）：3536-3549．DOI：10.2337/db06-0319.
［10］KIM T H，LEE S S，YOO J H，et al．The relationship between the regional abdominal adipose tissue distribution and the serum uric acid levels in people with type 2 diabetes mellitus［J］．Diabetol Metab Syndr，2012，4（1）：3．DOI：10.1186/1758-5996-4-3.
［11］MATTSSON S，THOMAS B J.Development of methods for body composition studies［J］．Phys Med Biol，2006，51（13）：R203-228．DOI：10.1088/0031-9155/51/13/r13.
［12］OKORODUDU D O，JUMEAN M F，MONTORI V M，et al．Diagnostic performance of body mass index to identify obesity as defined by body adiposity：a systematic review and meta-analysis［J］．Int J Obes （Lond），2010，34（5）：791-799．DOI：10.1038/ijo.2010.5.
［13］MI S Q，YIN P，HU N，et al．BMI，WC，WHtR，VFI and BFI：which indictor is the most efficient screening index on type 2 diabetes in Chinese community population［J］．Biomed Environ Sci，2013，26（6）：485-491．DOI：10.3967/0895-3988.2013.06.009.
［14］尹雪瑶，周嘉强，余丹，等．尿酸与腹型肥胖及代谢综合征相关性研究［J］．中华内科杂志，2014，53（1）：13-18．DOI：10.3760/cma.j.issn.0578-1426.2014.01.004.
YIN X Y，ZHOU J Q，YU D，et al．The correlation between serum uric acid level and abdominal obesity or metabolic syndrome［J］．Chin J Intern Med，2014，53（1）：13-18．DOI：10.3760/cma.j.issn.0578-1426.2014.01.004.
［15］MATSUURA F，YAMASHITA S，NAKAMURA T，et al．Effect of visceral fat accumulation on uric acid metabolism in male obese subjects：visceral fat obesity is linked more closely to overproduction of uric acid than subcutaneous fat obesity［J］．Metabolism，1998，47（8）：929-933．DOI：10.1016/s0026-0495（98）90346-8.

[1]	LI Zimeng, WANG Rong, CHEN Shuai, ZHAO Caili, WANG Xiaocong, WEN Yalu, LIU Long. Application of metaPRS and APOEε4 to Optimize Genetic Risk Prediction Modeling Strategy for Mild Cognitive Impairment [J]. Chinese General Practice, 2023, 26(25): 3104-3111.
[2]	Yizhen NIE, Zhaoqi YAN, Wei YAN, Hongmei FU, Xingjuan ZHAO, Hui YIN, Qunhong WU. A Clinical Study of Structural Properties of Osteosarcopenic Obesity Syndrome Using Multivariate Statistical Methods [J]. Chinese General Practice, 2022, 25(22): 2733-2739.
[3]	Chenxi ZHANG, Shengnan GUAN, Kai XIE, Kang ZHANG, Haifeng WANG. Distribution of Clinical Traditional Chinese Medicine Syndromes in Patients with Severe Community-acquired Pneumonia [J]. Chinese General Practice, 2022, 25(21): 2640-2645.
[4]	Fei YIN, Yun LIU, Xie SHEN. Development and Improvement of Nomograms Predicting the Prognosis in Patients with Severe Multiple Trauma [J]. Chinese General Practice, 2022, 25(20): 2498-2506.
[5]	WEI Xiaofei，QIN Xianjing，PENG Rong，FENG Jun，FENG Qiming. Efficiency of Mental Health Services Delivery in Township Hospitals of Guangxi Based on Data Envelopment Analysis　 [J]. Chinese General Practice, 2021, 24(4): 421-426.
[6]	CHEN Yichen，QU Xiaobin，SUN Lianghong，LI Xiaopan，CHEN Hanyi，CHEN Hua，ZHOU Yi，XIAO Shaotan. Liver Carcinoma-related Mortality and Potential Years of Life Lost among Residents in Pudong New Area of Shanghai between 2002 and 2019　 [J]. Chinese General Practice, 2021, 24(12): 1517-1522.
[7]	Wayne A Babchuk （writing），MA Lan，WANG Yang（translator），HAN Jianjun，XU Yanli，YANG Hui（reviser）. Fundamentals of Qualitative Analysis in Family Medicine　 [J]. Chinese General Practice, 2019, 22(26): 3145-3153.
[8]	ZHANG Yan-chun1，2，LIU Fang1*，PU Lin3，QIN Jiang-mei1，Kim Sweeny2. Effectiveness Prediction of Community-based Hypertension Management in China：an Analysis based on Risk Prediction Models　 [J]. Chinese General Practice, 2018, 21(17): 2082-2085.