儿童青少年体脂肪和瘦体重对心血管危险因素聚集的交互作用

董洋洋; 蔡蓉蓉; 白玲; 周金玉; 贾磊娜; 丁文清

doi:10.16835/j.cnki.1000-9817.2021.10.027

儿童青少年体脂肪和瘦体重对心血管危险因素聚集的交互作用

doi: 10.16835/j.cnki.1000-9817.2021.10.027

董洋洋^{1, 2},
蔡蓉蓉^{1, 2},
白玲^{1, 2},
周金玉^{1, 2},
贾磊娜^{1, 2},
丁文清^{1, 2, ,}

1.
宁夏医科大学公共卫生与管理学院，银川 750004
2.
宁夏环境因素与慢性病控制重点实验室

基金项目:

国家自然科学基金项目 81660565

详细信息

作者简介:
董洋洋(1993-)，女，河北邯郸人，在读硕士，主要研究方向为儿童青少年慢性流行病学

通讯作者:
丁文清，E-mail：dwqdz@163.com

中图分类号: R179 R725.4
计量
- 文章访问数: 520
- HTML全文浏览量: 231
- PDF下载量: 42
- 被引次数: 0
出版历程
- 收稿日期: 2021-03-12
- 修回日期: 2021-04-25
- 网络出版日期: 2021-10-25
- 刊出日期: 2021-10-25

Interaction between fat mass and fat free mass on the aggregation of cardiovascular disease risk factors among children and adolescents

DONG Yangyang^{1, 2},
CAI Rongrong^{1, 2},
BAI Ling^{1, 2},
ZHOU Jinyu^{1, 2},
JIA Leina^{1, 2},
DING Wenqing^{1, 2
, ,}

1.
School of Public Health and Management, Ningxia Medical University, Yinchuan(750004), China

摘要

摘要: 目的分析银川市儿童青少年体脂肪(FM)和瘦体重(FFM)对心血管危险因素(CVRFs)聚集的交互作用，为预防儿童青少年心血管疾病的发生提供科学依据。方法于2017—2020年使用整群抽样的方法选取银川市1 822名12~18岁儿童青少年，进行问卷调查、体格检查、体成分测定和实验室检测。采用二分类Logistic回归分析FM、FFM与CVRFs聚集的关系，并分析交互作用。结果调整性别和年龄后，高FM低FFM组和高FM高FFM组发生CVRFs聚集个数至少为1(CVRFs≥1)的风险是低FM低FFM组的2.01(95%CI=1.46~2.77)、3.64(95%CI=2.66~4.98)倍，CVRFs聚集个数至少为2(CVRFs≥2)的风险分别为1.67(95%CI=1.06~2.63)、4.20(95%CI=2.76~6.38)倍(P值均 < 0.05)；FM和FFM存在相乘交互作用，增加CVRFs≥1和CVRFs≥2的风险，调整后的OR值(95%CI)值分别为1.58(1.04~2.40)、1.95(1.12~3.42)(P值均 < 0.05)。结论高水平体脂肪和瘦体重对心血管危险因素聚集有相加和相乘交互作用, 增加了心血管危险因素聚集的风险。
- 脂肪组织 /
- 体重 /
- 心血管系统 /
- 回归分析 /
- 儿童 /
- 青少年
Abstract: Objective To analyze the interaction of fat mass (FM) and fat free mass (FFM) on the aggregation of cardiovascular disease risk factors (CVRFs) among children and adolescents in Yinchuan City, China, so as to provide scientific basis for the prevention of CVRFs and cardiovascular disease in children and adolescents. Methods A total of 1 822 children and adolescents aged 12 to 18 years in Yinchuan City were randomly selected for questionnaire survey, physical examination, body composition assessment and laboratory tests, through a cluster sampling method from 2017 to 2020. Binary Logistic regression was used to analyze the relationship between FM, FFM and the aggregation of CVRFs, and their interaction was analyzed. Results After adjusting for sex and age, the risk of having CVRFs aggregation ≥1 in high FM and low FFM group and high FM and high FFM group was 2.01(95%CI=1.46-2.77) and 3.64(95%CI=2.66-4.98) times higher than that in low FM and low FFM group, and the risk of having CVRFs aggregation ≥2 was 1.67(95%CI=1.06-2.63) and 4.20 (95%CI=2.76-6.38) times, respectively(P < 0.05). There was a multiplicative interaction between FM and FFM, which increased the risk of CVRFs aggregration ≥1 and ≥2. The adjusted OR and 95%CI were 1.58(1.04-2.40) and 1.95(1.12-3.42), respectively(P < 0.05). Conclusion The results indicated the additive and multiplicative interactions between high levels of fat mass and fat free mass on the aggregation of cardiovascular risk factors, which increased the risk of aggregation of cardiovascular risk factors.
- Adipose tissue /
- Body weight /
- Cardiovascular system /
- Regression analysis /
- Child /
- Adolescent

HTML全文

表 1 不同组别研究对象基本特征及生化指标比较(x±s)

Table 1. Comparison of basic characteristics and biochemical indexes of subjects in different groups(x±s)

组别	人数	年龄/岁	身高/cm	体重/kg	BMI/(kg·m^-2)	WC/cm	WHtR	FM/kg	FFM/kg
低FM低FFM	411	14.51±1.73	162.83±6.87	45.85±4.40	17.29±1.34	65.47±3.01	0.40±0.02	7.26±2.36	38.58±4.45
低FM高FFM	511	15.57±1.35	174.22±5.75	57.98±5.21	19.12±1.50	70.05±3.53	0.40±0.02	6.98±2.06	51.00±4.25
高FM低FFM	505	15.02±1.81	161.99±5.55	55.31±6.61	21.14±2.50	75.76±6.09	0.47±0.04	16.84±4.61	38.47±3.52
高FM高FFM	395	15.20±1.51	173.72±6.54	76.80±11.43	25.47±3.42	87.93±9.78	0.51±0.06	21.32±7.88	55.48±6.95
F/H值		33.77	547.09	1 292.82	952.81	1 053.93	864.24	1 021.41	1 412.84
P值		< 0.01	< 0.01	< 0.01	< 0.01	< 0.01	< 0.01	< 0.01	< 0.01

组别	人数	FPG/ (mmol·L^-1)	TC/ (mmol·L^-1)	TG/ (mmol·L^-1)^*		HDL-C/ (mmol·L^-1)	LDL-C/ (mmol·L^-1)	SBP/ mm Hg	DBP/ mm Hg
低FM低FFM	411	4.75±0.60	3.77±0.83	0.87(0.71, 1.07)		1.44±0.36	2.00±0.65	107.85±9.72	66.20±7.18
低FM高FFM	511	4.79±0.85	3.88±0.91	0.87(0.68, 1.08)		1.44±0.38	2.12±0.74	112.46±10.43	66.63±8.13
高FM低FFM	505	4.74±0.59	4.08±0.96	0.98(0.77, 1.25)		1.46±0.41	2.22±0.75	108.41±9.81	68.73±7.41
高FM高FFM	395	4.84±0.62	4.08±0.97	1.10(0.82, 1.45)		1.28±0.32	2.38±0.87	120.14±10.97	70.57±8.32
F/H值		1.81	12.34	116.67		21.61	17.73	126.87	28.48
P值		0.14	< 0.01	< 0.01		< 0.01	< 0.01	< 0.01	< 0.01
注： 1 mm Hg=0.133 kPa；*为M(P₂₅，P₇₅)。

下载: 导出CSV

表 2 不同体脂肪和瘦体重分组儿童青少年心血管危险因素及其聚集检出率比较

Table 2. Comparison detection rate of cardiovascular disease risk factors and aggregation based on fat mass and fat free mass subgroups amongchildren and adolescents

组别	人数	高血糖	高TC血症	高TG血症	高LDL-C	低HDL-C	高血压	CVRFs≥1	CVRFs≥2
低FM低FFM	411	38(10.2)	28(6.9)	22(5.5)	15(3.7)	31(7.7)	33(8.0)	121(31.9)	37(9.3)
低FM高FFM	511	65(14.8)	43(8.5)	33(6.6)	27(5.4)	52(10.4)	38(7.4)	185(40.4)	58(11.8)
高FM低FFM	505	32(7.6)	61(12.3)	80(16.1)	43(8.7)	55(11.1)	57(11.3)	214(47.9)	81(16.9)
高FM高FFM	395	42(12.2)	51(13.0)	93(23.8)	47(12.0)	94(24.0)	99(25.1)	249(66.2)	112(30.2)
χ²值		12.06	11.94	84.61	24.33	57.14	77.39	98.39	73.14
P值		0.01	0.01	< 0.01	< 0.01	< 0.01	< 0.01	< 0.01	< 0.01
注： ()内数字为检出率/%；血糖及部分血脂指标数据存在缺失值。

下载: 导出CSV

表 3 不同模型下儿童青少年体脂肪和瘦体重与心血管危险因素聚集的关系(n=1 822)

Table 3. Relationship between fat mass, fat free mass and aggregation of cardiovascular disease risk factors in different models among children and adolescents(n=1 822)

模型	自变量	CVRFs≥1		CVRFs≥2
模型	自变量	未调整 OR值(OR值95%CI)	调整 OR值(OR值95%CI)	未调整 OR值(OR值95%CI)	调整 OR值(OR值95%CI)
1	FM
	低	1.00	1.00	1.00	1.00
	高	2.39(1.95~2.92)^a	2.59(2.07~3.25)^a	2.65(2.02~3.47)^a	2.56(1.90~3.44)^a
	FFM
	低	1.00	1.00	1.00	1.00
	高	1.76(1.44~2.16)^a	1.40(1.08~1.82)^b	1.80(1.38~2.34)^a	1.90(1.33~2.72)^a
2	低FM低FFM	1.00	1.00	1.00	1.00
	低FM高FFM	1.45(1.09~1.92)^b	1.15(0.84~1.57)	1.31(0.85~2.02)	1.29(0.80~2.07)
	高FM低FFM	1.96(1.47~2.60)^a	2.01(1.46~2.77)^a	1.98(1.31~3.00)^b	1.67(1.06~2.63)^b
	高FM高FFM	4.18(3.09~5.67)^a	3.64(2.66~4.98)^a	4.22(2.82~6.32)^a	4.20(2.76~6.38)^a
3	FM	1.96(1.47~2.60)^a	2.01(1.46~2.77)^a	1.98(1.31~3.00)^b	1.67(1.06~2.63)^b
	FFM	1.45(1.09~1.92)^b	1.15(0.84~1.57)	1.31(0.85~2.02)	1.29(0.80~2.07)
	FM×FFM	1.48(0.99~2.21)	1.58(1.04~2.40)^b	1.63(0.95~2.81)	1.95(1.12~3.42)^b
注： b P < 0.05，a P < 0.01。

下载: 导出CSV

参考文献(27)

[1]	NAGHAVI M, ABAJOBIR A A, ABBAFATI C, et al. Global, regional, and national age-sex specifc mortality for 264 causes of death, 1980-2016: a systematic analysis for the global burden of disease study 2016[J]. Lancet, 2017, 390(10100): 1151-1210. doi: 10.1016/S0140-6736(17)32152-9
[2]	CHUNG S T, ONUZURUIKE A U, MAGGE S N. Cardiometabolic risk in obese children[J]. Ann Ny Acad Sci, 2018, 1411(1): 166-183. doi: 10.1111/nyas.13602
[3]	O'DONNELL M J, XAVIER D, LIU L, et al. Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries(the INTERSTROKE study): a case-control study[J]. Lancet, 2010, 376(9735): 112-123. doi: 10.1016/S0140-6736(10)60834-3
[4]	ONG K L, TSO A W K, LAM K S L, et al. Gender difference in blood pressure control and cardiovascular risk factors in Americans with diagnosed hypertension[J]. Hypertension, 2008, 51(4): 1142-1148. doi: 10.1161/HYPERTENSIONAHA.107.105205
[5]	KOSKINEN J, MAGNUSSEN C G, SINAIKO A, et al. Childhood age and associations between childhood metabolic syndrome and adult risk for metabolic syndrome, type 2 diabetes mellitus and carotid intima media thickness: the international childhood cardiovascular cohort consortium[J]. J Am Heart Assoc, 2017, 6(8): e005632. http://europepmc.org/abstract/MED/28862940
[6]	MCCRINDLE B W, MANLHIOT C, MILLAR K, et al. Population tre-nds toward increasing cardiovascular risk factors in Canadian adolescents[J]. J Pediatr, 2010, 157(5): 837-843. doi: 10.1016/j.jpeds.2010.05.014
[7]	李双双, 马传伟, 席波. 中国7~17岁儿童青少年1993—2011年血压偏高变化趋势分析[J]. 中国学校卫生, 2016, 37(10): 1449-1452. doi: 10.16835/j.cnki.1000-9817.2016.10.003 LI S S, MA C W, XI B. Trends in elevated blood pressure among Chinese children and adolescents, 1993-2011[J]. Chin J Sch Health, 2016, 37(10): 1449-1452. doi: 10.16835/j.cnki.1000-9817.2016.10.003
[8]	丁文清, 董虹孛, 米杰. 中国儿童青少年血脂异常流行现状Meta分析[J]. 中华流行病学杂志, 2015, 36(1): 71-77. doi: 10.3760/cma.j.issn.0254-6450.2015.01.017 DING W Q, DONG H B, MI J. Prevalenee of dyslipidemia in Chinese children and adolescents: a Meta-analysis[J]. Chin J Epidemiol, 2015, 36(1): 71-77. doi: 10.3760/cma.j.issn.0254-6450.2015.01.017
[9]	SEO Y, CHOI M, KANG J, et al. Cardiovascular disease risk factor clustering in children and adolescents: a prospective cohort study[J]. Arch Dis Child, 2018, 103(10): 968-973. doi: 10.1136/archdischild-2017-313226
[10]	XIONGFEI L, XIANHUA C, JING L, et al. Study on body composition and its correlation with obesity: a cohort study in 5121 Chinese Han participants[J]. Medicine, 2018, 97(21): e10722. doi: 10.1097/MD.0000000000010722
[11]	SERRANO N C, SUAREZ D P, SILVA A R, et al. Association between body fat mass and cardiometabolic risk in children and adolescents in Bucaramanga, Colombia[J]. Int J Pediatr Adolesc Med, 2019, 6(4): 135-141. doi: 10.1016/j.ijpam.2019.06.004
[12]	KIM J H, PARK Y S. Low muscle mass is associated with metabolic syndrome in Korean adolescents: the Korea national health and nutrition examination survey 2009-2011[J]. Nutr Res, 2016, 36(12): 1423-1428. doi: 10.1016/j.nutres.2016.09.013
[13]	BURROWS R, CORREA-BURROWS P, REYES M, et al. High cardiometabolic risk in healthy chilean adolescents: associations with anthropometric, biological and lifestyle factors[J]. Public Health Nutr, 2016, 19(3): 486-493. doi: 10.1017/S1368980015001585
[14]	GRACIA-MARCO L, MORENO L A, RUIZ J R, et al. Body composition indices and single and clustered cardiovascular disease risk factors in adolescents: providing clinical-based cut-points[J]. Prog Cardiovasc Dis, 2016, 58(5): 555-564. doi: 10.1016/j.pcad.2015.11.002
[15]	全国学生体质与健康调研组. 2014年全国学生体质与健康调研手册[M]. 北京: 高等教育出版社, 2014. National Student Physical Fitness and Health Investigation Group. 2014 national student physical fitness and health investigation manual[M]. Beijing: Higher Education Press, 2014.
[16]	FALKNER B, DANIELS S R. Summary of the fourth report on the diagnosis, evaluation, and treatment of high blood pressure in children and adolescents[J]. Hypertension, 2004, 44(4): 387-388. doi: 10.1161/01.HYP.0000143545.54637.af
[17]	范晖, 闫银坤, 米杰. 中国3~17岁儿童性别、年龄别和身高别血压参照标准[J]. 中华高血压杂志, 2017, 25(5): 428-435. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGZ201705010.htm FAN H, YAN Y K, MI J. Updating blood pressure references for Chinese children aged 3-17 years[J]. Chin J Hypertens, 2017, 25(5): 428-435. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGZ201705010.htm
[18]	ARIZA A J. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report[J]. Pediatrics, 2011, 128(Suppl 5): S213-S256. http://pedclerk.bsd.uchicago.edu/sites/pedclerk.uchicago.edu/files/uploads/cards.pdf
[19]	DICESARE C A, ADAMS J R, CLAYTOR R P, et al. Relationship between proxies for type Ⅱ fiber type and resting blood pressure in division Ⅰ American football athletes[J]. Int J Health Sci, 2017, 11(2): 16-20. http://www.ijhs.org.sa/index.php/journal/article/download/1788/pdf
[20]	FISHER G, WINDHAM S T, GRIFFIN P, et al. Associations of human skeletal muscle fiber type and insulin sensitivity, blood lipids, and vascular hemodynamics in a cohort of premenopausal women[J]. Eur J Appl Physiol, 2017, 117(7): 1413-1422. doi: 10.1007/s00421-017-3634-9
[21]	PEI X, HONG C, YINKUN Y, et al. High BMI with adequate lean mass is not associated with cardiometabolic risk factors in children and adolescents[J]. J Nutr, 2020(7): nxaa328. http://www.researchgate.net/publication/347577793_High_BMI_with_Adequate_Lean_Mass_Is_Not_Associated_with_Cardiometabolic_Risk_Factors_in_Children_and_Adolescents
[22]	BROCHU M, MATHIEU M E, KARELIS A D, et al. Contribution of the lean body mass to insulin resistance in postmenopausal women with visceral obesity: a monet study[J]. Obesity, 2012, 16(5): 1085-1093. http://www.onacademic.com/detail/journal_1000034766108710_f414.html
[23]	PRAMYOTHIN P, LIMPATTANACHART V, DAWILAI S, et al. Fat-free mass, metabolically healthy obesity, and type 2 diabetes in severely obese asian adults[J]. Endocr Pract, 2017, 23(8): 915-922. doi: 10.4158/EP171792.OR
[24]	CORREA-RODRÍGUEZ M, RAMÍREZ-VÉLEZ R, CORREA-BAUTISTA J E, et al. Association of muscular fitness and body fatness with cardiometabolic risk factors: the fuprecol study[J]. Nutrients, 2018, 10(11): 1742. doi: 10.3390/nu10111742
[25]	COLPITTS B H, BOUCHARD D R, KESHAVARZ M, et al. Does lean body mass equal health despite body mass index?[J]. Scand J Med Sci Spor, 2020, 30(4): 672-679. doi: 10.1111/sms.13605
[26]	PELLEGRINELLI V, ROUAULT C, RODRIGUEZ-CUENCA S, et al. Human adipocytes induce inflammation and atrophy in muscle cells during obesity[J]. Diabetes, 2015, 64(9): 3121-3134. doi: 10.2337/db14-0796
[27]	JAFFRIN M Y, MOREL H. Body fluid volumes measurements by impedance: a review of bioimpedance spectroscopy (BIS) and bioimpedance analysis (BIA) methods[J]. Med Eng Phys, 2008, 30(10): 1257-1269. doi: 10.1016/j.medengphy.2008.06.009