儿童青少年身体脂肪分布与抑郁和社交焦虑的关联：基于双能X线检测的横断面研究

doi:10.19723/j.issn.1671-167X.2023.03.007

摘要/Abstract

摘要：

目的: 探讨儿童青少年抑郁、社交焦虑的现状，并分析儿童青少年脂肪分布与抑郁和社交焦虑的关联。方法: 采取分层整群随机抽样法纳入北京市7~18岁儿童青少年1 412名，使用双能X线吸收法获得其脂肪分布，使用儿童抑郁量表和儿童社交焦虑量表评价其抑郁和社交焦虑情况，采用多元线性回归和限制性立方样条分析估计儿童青少年脂肪分布与其抑郁、社交焦虑的线性与非线性关联。结果: 13.1%和31.1%的儿童青少年分别存在抑郁症状和社交焦虑症状，且男生、低年龄组的抑郁和社交焦虑检出率显著低于女生、高年龄组。儿童青少年的总脂肪率、Android脂肪率、Gynoid脂肪率、Android与Gynoid脂肪比(Android-to-Gynoid fat ratio，AOI)与抑郁和社交焦虑不存在显著性线性关联，但总脂肪率和Gynoid脂肪率与抑郁的非线性关联显著，表现为倒“U”型曲线关系，切点分别为26.8%和30.9%。脂肪分布与抑郁、社交焦虑的关联在不同性别和高低年龄组间差异不存在统计学意义。结论: 儿童青少年的脂肪分布与抑郁和社交焦虑不存在显著性线性关联; 脂肪分布与抑郁呈现倒“U”型曲线，主要表现在总脂肪率和Gynoid脂肪率上，且这种趋势在不同性别和不同年龄组上均表现出一致性。将儿童青少年的脂肪分布维持在一个合适的水平，是未来儿童青少年抑郁、社交焦虑防控关注的方向。

关键词: 抑郁, 社交焦虑, 体脂分布, 限制性立方样条

Abstract:

Objective: To investigate the status of depression and social anxiety in children and adolescents, and to analyze the association between body fat distribution and depression, social anxiety in children and adolescents. Methods: A total of 1 412 children aged 7 to 18 years in Beijing were included by stratified cluster random sampling method. Body fat distribution, including total body fat percentage (total BF%), Android BF%, Gynoid BF% and Android-to-Gynoid fat ratio (AOI), were obtained by dual-energy X-ray absorption method. Depression and social anxiety were evaluated by Children Depression Inventory and Social Anxiety Scale for Children. Multivariate linear regression and restricted cubic spline analysis were used to estimate the linear and non-linear correlation between body fat distribution and depression and social anxiety. Results: 13.1% and 31.1% of the children and adolescents had depressive symptoms and social anxiety symptoms respectively, and the detection rate of depression and social anxiety in the boys and young groups was significantly lower than those in the girls and old groups. There was no significant linear correlation between total BF%, Android BF%, Gynoid BF%, AOI and depression and social anxiety in the children and adolescents. However, total BF% and Gynoid BF% had significant nonlinear correlation with depression, showing an inverted U-shaped curve relationship with the tangent points of 26.8% and 30.9%, respectively. In terms of the nonlinear association of total BF%, Android BF%, Gynoid BF% and AOI with depression and social anxiety, the change trends of the boys and girls, low age group and high age group were consistent. The overall anxiety risk HR of body fat distribution in the boys was significantly higher than that in the girls, and the risk HR of depression and social anxiety were significantly higher in the high age group than those in the low age group. Conclusion: There was no significant linear correlation between body fat distribution and depression and social anxiety in children and adolescents. Total BF% and depression showed an inverted U-shaped curve, mainly manifested in Gynoid BF%, and this trend was consistent in different genders and different age groups. Maintaining children and adolescents' body fat distribution at an appropriate level is the future direction of the prevention and control of depression and social anxiety in children and adolescents.

Key words: Depression, Social anxiety, Body fat distribution, Restrictive cubic splines

中图分类号:

R179

袁雯,张奕,陈力,蒋家诺,陈曼曼,刘婕妤,马涛,马奇,崔孟杰,郭桐君,王鑫鑫,董彦会,马军. 儿童青少年身体脂肪分布与抑郁和社交焦虑的关联：基于双能X线检测的横断面研究[J]. 北京大学学报（医学版）, 2023, 55(3): 429-435.

Wen YUAN,Yi ZHANG,Li CHEN,Jia-nuo JIANG,Man-man CHEN,Jie-yu LIU,Tao MA,Qi MA,Meng-jie CUI,Tong-jun GUO,Xin-xin WANG,Yan-hui DONG,Jun MA. Association of body fat distribution with depression and social anxiety in children and adolescents: A cross-sectional study based on dual-energy X-ray detection[J]. Journal of Peking University (Health Sciences), 2023, 55(3): 429-435.

图/表 5

表1

表2

图1

图2

图3

参考文献 31

1	Charlson F , van Ommeren M , Flaxman A , et al.New WHO pre-valence estimates of mental disorders in conflict settings: Asyste- matic review and meta-analysis[J].Lancet,2019,394(10194):240-248. doi: 10.1016/S0140-6736(19)30934-1
2	Lu J , Xu XF , Huang YQ , et al.Prevalence of depressive disorders and treatment in China: A cross-sectional epidemiological study[J].Lancet Psychiat,2021,8(11):981-990. doi: 10.1016/S2215-0366(21)00251-0
3	Clarke DM , Currie KC .Depression, anxiety and their relationship with chronic diseases: A review of the epidemiology, risk and treatment evidence[J].Med J Australia,2009,190(7):S54-S60.
4	Blaine B .Does depression cause obesity? A meta-analysis of longitudinal studies of depression and weight control[J].J Health Psychol,2008,13(8):1190-1197. doi: 10.1177/1359105308095977
5	Dixon JB , Dixon ME , O'Brien PE .Depression in association with severe obesity: Changes with weight loss[J].Arch Intern Med,2003,163(17):2058-2065. doi: 10.1001/archinte.163.17.2058
6	Quek YH , Tam WWS , Zhang MWB , et al.Exploring the association between childhood and adolescent obesity and depression: A meta-analysis[J].Obes Rev,2017,18(7):742-754. doi: 10.1111/obr.12535
7	Rao WW , Zong QQ , Zhang JW , et al.Obesity increases the risk of depression in children and adolescents: Results from a systema-tic review and meta-analysis[J].J Affect Disorders,2020,267,78-85. doi: 10.1016/j.jad.2020.01.154
8	Cole TJ , Bellizzi MC , Flegal KM , et al.Establishing a standard definition for child overweight and obesity worldwide: International survey[J].BMJ,2000,320(7244):1240-1243. doi: 10.1136/bmj.320.7244.1240
9	国家卫生和计划生育委员会. 学龄儿童青少年超重与肥胖筛查[S]. (2018-08-01)[2023-01-05]. https://www.chinacdc.cn/jkzt/yyhspws/xzdc/201804/P020180418380884895984.pdf.
10	Javed A , Jumean M , Murad MH , et al.Diagnostic performance of body mass index to identify obesity as defined by body adiposity in children and adolescents: A systematic review and meta-analysis[J].Pediatr Obes,2015,10(3):234-244. doi: 10.1111/ijpo.242
11	Romero-Corral A , Somers VK , Sierra-Johnson J , et al.Accuracy of body mass index in diagnosing obesity in the adult general population[J].Int J Obesity,2008,32(6):959-966. doi: 10.1038/ijo.2008.11
12	Zhou Y , Hoglund P , Clyne N .Comparison of DEXA and bioimpedance for body composition measurements in nondialysis patients with CKD[J].J Ren Nutr,2019,29(1):33-38. doi: 10.1053/j.jrn.2018.05.003
13	Liu XJ , Zhang DD , Liu Y , et al.Dose response association between physical activity and incident hypertension: A systematic review and meta-analysis of cohort studies[J].Hypertension,2017,69(5):813-820. doi: 10.1161/HYPERTENSIONAHA.116.08994
14	Ye SY , Zhu CN , Wei C , et al.Associations of body composition with blood pressure and hypertension[J].Obesity,2018,26(10):1644-1650. doi: 10.1002/oby.22291
15	Kovacs M .The childrens depression inventory (CDI)[J].Psychopharmacol Bull,1985,21(4):995-998.
16	Helsel WJ , Matson JL .The assessment of depression in children: The internal structure of the child depression inventory (CDI)[J].Behav Res Ther,1984,22(3):289-298. doi: 10.1016/0005-7967(84)90009-3
17	Lagreca AM , Dandes SK , Wick P , et al.Development of the social anxiety scale for children: Reliability and concurrent validity[J].J Clin Child Psychol,1988,17(1):84-91. doi: 10.1207/s15374424jccp1701_11
18	Zhao G , Ford ES , Dhingra S , et al.Depression and anxiety among US adults: Associations with body mass index[J].Int J Obesity,2009,33(2):257-266. doi: 10.1038/ijo.2008.268
19	陈曼曼, 马莹, 苏彬彬, 等.北京市7~18岁儿童青少年体成分百分位值变化特征[J].中国学校卫生,2021,42(11):1703-1707.
20	He W , James S A , Merli MG , et al.An increasing socioeconomic gap in childhood overweight and obesity in China[J].Am J Public Health,2014,104(1):E14-E22. doi: 10.2105/AJPH.2013.301669
21	Chung KH , Chiou HY , Chen YH .Psychological and physiological correlates of childhood obesity in Taiwan[J].Sci Rep,2015,5,17439. doi: 10.1038/srep17439
22	Merikangas AK , Mendola P , Pastor PN , et al.The association between major depressive disorder and obesity in US adolescents: Results from the 2001-2004 National Health and Nutrition Exa-mination Survey[J].J Behav Med,2012,35(2):149-154. doi: 10.1007/s10865-011-9340-x
23	陆迪菲, 袁振芳, 杨丽华, 等.肥胖人群焦虑抑郁情况与肥胖程度相关性的调查分析[J].中国糖尿病杂志,2019,27(8):592-596.
24	Chung S .Body composition analysis and references in children: Clinical usefulness and limitations[J].Eur J Clin Nutr,2019,73(2):236-242. doi: 10.1038/s41430-018-0322-8
25	Rapuano KM , Laurent JS , Hagler DJ , et al.Nucleus accumbens cytoarchitecture predicts weight gain in children[J].Proc Natl Acad Sci USA,2020,117(43):26977-26984. doi: 10.1073/pnas.2007918117
26	Dionysopoulou S , Charmandari E , Bargiota A , et al.The role of hypothalamic inflammation in diet-induced obesity and its association with cognitive and mood disorders[J].Nutrients,2021,13(2):498. doi: 10.3390/nu13020498
27	Zhang JH , Lam SP , Li SX , et al.A community-based study on the association between insomnia and hypothalamic-pituitary-adrenal axis: Sex and pubertal influences[J].J Clin Endocr Metab,2014,99(6):2277-2287. doi: 10.1210/jc.2013-3728
28	Kohler CA , Freitas TH , Maes M , et al.Peripheral cytokine and chemokine alterations in depression: A meta-analysis of 82 studies[J].Acta Psychiat Scand,2017,135(5):373-387. doi: 10.1111/acps.12698
29	Jantaratnotai N , Mosikanon K , Lee Y , et al.The interface of depression and obesity[J].Obes Res Clin Pract,2017,11(1):1-10.
30	Pierce GL , Kalil GZ , Ajibewa T , et al.Anxiety independently contributes to elevated inflammation in humans with obesity[J].Obesity,2017,25(2):286-289.
31	Dos Santos RRG , Forte GC , Mundstock E , et al.Body composition parameters can better predict body size dissatisfaction than body mass index in children and adolescents[J].Eat Weight Disord,2020,25(5):1197-1203.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Items	Total	Gender				Age group
Items	Total	Boys	Girls	t	P	7-12 years	13-18 years	t	P
Sample size	1 412	716	696			688	724
Age/years	11.93±3.60	12.43±3.35	12.35±3.29			9.46±1.7	15.18±1.66
Height/cm	152.77±17.57	158.24±17.09	152.33±13.27	7.26	< 0.001	142.49±11.07	167.53±7.26	-49.97	< 0.001
Weight/kg	49.33±19.09	53.98±19.99	43.60±16.15	5.57	< 0.001	38.63±11.82	63.39±15.06	-34.45	< 0.001
BMI/(kg/m²)	20.34±4.72	20.85±4.78	20.42±4.65	1.71	0.088	18.67±3.79	22.51±4.76	-16.80	< 0.001
Body composition
BF%	0.29±0.08	0.26±0.09	0.32±0.07	-12.92	< 0.001	0.30±0.07	0.28±0.09	4.62	< 0.001
Android BF%	0.28±0.12	0.26±0.13	0.30±0.11	-7.03	< 0.001	0.28±0.11	0.28±0.12	-0.56	0.573
Gynoid BF%	0.32±0.09	0.28±0.09	0.36±0.06	-17.40	< 0.001	0.34±0.08	0.30±0.10	7.34	< 0.001
AOI	0.34±0.11	0.36±0.12	0.32±0.09	7.08	< 0.001	0.33±0.10	0.35±0.11	-4.41	< 0.001
CDI score	10.80±6.92	10.54±6.39	11.06±7.40	-1.40	0.163	8.77±5.74	12.73±7.38	-11.29	< 0.001
SAS-C score	5.66±4.16	5.14±3.89	6.20±4.39	-4.82	< 0.001	4.85±3.79	6.43±4.36	-7.29	< 0.001
Depression	199 (13.1)	87 (11.2)	112 (15.0)	4.53	0.033	58 (8.4)	141 (19.5)	35.54	< 0.001
Social anxiety	439 (31.1)	153 (26.2)	286 (36.1)	15.84	< 0.001	188 (22.2)	251 (39.5)	40.08	< 0.001

Items	Total		Boys		Girls
Items	β (95%CI)	P	β (95%CI)	P	β (95%CI)	P
Depression
BF%	-0.36 (-0.13, 0.52)	0.421	-0.02 (-0.14, 0.09)	0.713	-0.05 (-0.20, 0.10)	0.520
Android BF%	-0.12 (-0.51, 0.27)	0.536	-0.46 (-1.01, 0.1)	0.109	-0.20 (-0.78, 0.38)	0.501
Gynoid BF%	0.07 (-0.19, 0.32)	0.621	0.30 (-0.09, 0.68)	0.128	0.07 (-0.32, 0.46)	0.720
AOI	0.02 (-0.17, 0.21)	0.862	0.17 (-0.08, 0.43)	0.182	0.17 (-0.16, 0.49)	0.319
Social anxiety
BF%	-0.02 (-0.11, 0.07)	0.695	-0.02 (-0.13, 0.10)	0.129	-0.03 (-0.19, 0.12)	0.120
Android BF%	-0.18 (-0.57, 0.22)	0.385	-0.52 (-1.10, 0.05)	0.073	-0.08 (-0.68, 0.51)	0.788
Gynoid BF%	0.10 (-0.17, 0.36)	0.469	0.33 (-0.06, 0.72)	0.098	0.003 (-0.40, 0.39)	0.982
AOI	0.06 (-0.13, 0.26)	0.527	0.22 (-0.05, 0.48)	0.105	0.09 (-0.24, 0.42)	0.601

Items	6-12 years				13-18 years
Items	β (95%CI)		P		β (95%CI)	P
Depression
BF%	-0.08 (-0.19, 0.04)		0.141		0.004 (-0.14, 0.15)	0.153
Android BF%	-0.50 (-0.98, -0.02)		0.040		0.06 (-0.57, 0.70)	0.845
Gynoid BF%	0.26 (-0.06, 0.57)		0.110		-0.04 (-0.47, 0.39)	0.865
AOI	0.23 (-0.03, 0.49)		0.082		0.01 (-0.28, 0.31)	0.926
Social anxiety
BF%	-0.11 (-0.23, 0.02)		0.085		-0.07 (-0.08, 0.21)	0.211
Android BF%	-0.72 (-1.24, -0.20)		0.007		0.27 (-0.35, 0.88)	0.395
Gynoid BF%	0.36 (0.02, 0.71)		0.037		-0.14 (-0.56, 0.27)	0.499
AOI	0.31 (0.02, 0.59)		0.034		-0.03 (-0.32, 0.26)	0.824

[1]	张紫薇,花语蒙,刘爱萍. 中国中老年人群抑郁症状、缺血性心血管疾病10年风险对心血管疾病的联合影响[J]. 北京大学学报（医学版）, 2023, 55(3): 465-470.
[2]	汪雨欣,邓宇含,谭银亮,刘宝花. 应激性血糖升高对重症监护病房患者28 d全因死亡风险的预测价值[J]. 北京大学学报（医学版）, 2023, 55(3): 442-449.
[3]	王婷,李乔晟,刘皓冉,简伟研. 人格特征、城乡差异与抑郁症状变化的关系[J]. 北京大学学报（医学版）, 2023, 55(3): 385-391.
[4]	陆林,刘晓星,袁凯. 中国脑科学计划进展[J]. 北京大学学报（医学版）, 2022, 54(5): 791-795.
[5]	樊理诗,高敏,Edwin B.FISHER,孙昕霙. 北京市通州区和顺义区747例2型糖尿病患者生存质量影响因素[J]. 北京大学学报（医学版）, 2021, 53(3): 523-529.
[6]	王一帆,范稹,成姚斌,金月波,霍阳,何菁. 原发性干燥综合征患者睡眠障碍的相关影响因素[J]. 北京大学学报（医学版）, 2020, 52(6): 1063-1068.
[7]	耿研,宋志博,张晓慧,邓雪蓉,王昱,张卓莉. 银屑病关节炎抑郁和焦虑患病情况及相关因素[J]. 北京大学学报（医学版）, 2020, 52(6): 1048-1055.
[8]	易端,朱薇,孟秀丽,刘晓光,李水清,祝斌,贾东林. 慢性腰腿痛患者微创术前焦虑,抑郁状态及相关影响因素分析[J]. 北京大学学报（医学版）, 2020, 52(2): 285-289.
[9]	刘颖,曾祥柱,王筝,张函,王希林,袁慧书. 三维动脉自旋标记技术评价抑郁合并高血压患者脑血流灌注[J]. 北京大学学报（医学版）, 2019, 51(2): 260-264.
[10]	雷杰，刘木清，傅开元. 睡眠问题、焦虑及压力是颞下颌关节紊乱病肌筋膜疼痛发病的风险指标[J]. 北京大学学报(医学版), 2016, 48(4): 692-696.
[11]	余灿清，陈怡平，吕筠，郭彧，Paul Sherliker，卞铮，周汇燕，谭云龙，陈君石，陈铮鸣，李立明. 中国30~79岁成人抑郁障碍与冠心病和脑卒中的关联[J]. 北京大学学报(医学版), 2016, 48(3): 465-471.
[12]	刘懿萱, 张永燊, 段丽萍, 张璐, 杨长青. 先天抑郁对大鼠幼年结肠乙酸刺激致慢性内脏高敏感的影响[J]. 北京大学学报（医学版）, 2015, 47(2): 289-294.
[13]	张舸, 赵绵松, 夏蓉晖, 王玉华, 张国华. 类风湿关节炎患者氧化应激与抑郁情绪的关系[J]. 北京大学学报（医学版）, 2012, 44(2): 199-203.
[14]	梁建辉, 王小平, 陆颖, 刘锐克, 张旗, 孙红蕾, 李凌江. 抗抑郁剂对小鼠探究行为、自主活动性以及隔离攻击行为的影响[J]. 北京大学学报（医学版）, 2003, 35(1): 54-60.