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Journal of Peking University (Health Sciences) ›› 2026, Vol. 58 ›› Issue (2): 319-326. doi: 10.19723/j.issn.1671-167X.2026.02.015

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Correlational research on body fat rate and skeletal muscle rate with depression in the population of assisted reproduction

Xiaohuan SONG1, Guiying LUO2, Jieyu WANG2, Yuedi JIA1, Fei JIANG3, Mengli ZHU3, Danni WANG1,*()   

  1. 1. Department of Health Promotion and Behavioral Sciences, School of Public Health, Anhui Medical University, Hefei 230032, China
    2. Centre for Reproductive Medicine, The First Affiliated Hospital of Anhui Medical University, Hefei 230000, China
    3. Department of Nutrition and Food Hygiene, School of Public Health, Anhui Medical University, Hefei 230032, China
  • Received:2024-03-26 Online:2026-04-18 Published:2025-09-24
  • Contact: Danni WANG
  • Supported by:
    the Youth Program of the National Natural Science Foundation of China(72004001); the Anhui University Scientific Research Humanities Project(2022AH050627)

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Abstract:

Objective: To investigate the relationship between body fat rates and skeletal muscle rates with depression among patients undergoing assisted reproductive technology (ART) treatments. Methods: A total of 885 infertility patients who underwent ART treatment at the Center for Reproductive Medicine of the First Affiliated Hospital of Anhui Medical University from July to October, 2022 were selected using the convenience sampling method. The basic information of the patients was investigated, depression was investigated using the patient health questionnaire-9 (PHQ-9), and human adiposity and body skeletal muscle rate data were measured using the InBody instrument with the principle of bioelectrical impedance analysis (BIA). Multiple linear regression, generalized linear model, and trend test were used to investigate the association between adiposity, skeletal muscle mass, and depression in the assisted reproduction population, as well as the dose-response relationship using restricted cubic spline (RCS) analysis. Results: The mean detection rate of depression in the ART population was 52.0%, with 55.5% in women and 45.5% in men. The average body fat rate was 28.01%, and the average body skeletal muscle rate was 39.73%. After correcting for confounders, the body fat rate was observed to be positively associated with depression (β=0.07, 95%CI: 0.01, 0.14), and the body skeletal muscle rate was negatively associated with depression (β=-0.12, 95%CI: -0.24, -0.01). Trend-based tests showed a highly significant monotonically increasing trend in depression with the increasing body fat rate and the decreasing body skeletal muscle rate. These associations were significant (P < 0.05) in the male population and in the assisted reproduction population aged >30 years. No significant non-linear associations were found between the body fat rate, the skeletal muscle rate and depression in the overall ART-treated population (Pnon-linear>0.05). Conclusion: The patients undergoing ART have a higher rate of depression detection, and their body fat and skeletal muscle rates are associated with the risk of depression in ART patients. Interventions, such as weight control, body fat reduction, and an exercise diet that increases skeletal muscle and other body components are expected to reduce the incidence of depression in assisted reproduction.

Key words: Assisted reproduction, Fat, Depression, Skeletal muscle, Restricted cubic spline

CLC Number: 

  • R715.3

Table 1

Basic information of the patients"

Characteristic Total (n=885) Male (n=312) Female (n=573) t/χ2 P value
Age/years, ${\bar x}$±s 30.82±4.37 31.1±1.41 30.7±4.35 -1.337 0.181
Education level, n (%) 0.863 0.065
  Below junior high school 260 (9.4) 86 (27.6) 174 (30.4)
  High school or secondary school 335 (37.9) 123 (39.4) 212 (37.0)
  Bachelor’s degree and above 290 (32.8) 103 (33.0) 187 (32.6)
Annual income, n (%) 75.446 < 0.001
  Less than 30 000 yuan 341 (38.5) 81 (26.0) 260 (45.4)
  30 000-100 000 yuan 401 (45.3) 138 (44.2) 263 (45.9)
  More than 100 000 yuan 143 (16.2) 93 (29.8) 50 (8.7)
Type of marriage, n (%) 7.083 0.008
  First marriage family 796 (89.9) 292 (93.6) 504 (88.0)
  Reorganized family 89 (10.1) 20 (6.4) 69 (12.0)
Infertility causes, n (%) 9.448 0.024
  Male 142 (16.0) 59 (18.9) 83 (14.5)
  Female 329 (37.2) 97 (31.3) 232 (40.5)
  Both parties have 210 (23.7) 74 (23.7) 136 (23.7)
  Unknown cause 204 (23.1) 82 (26.3) 122 (21.3)
Families’ perceptions of ART, n (%) 3.365 0.067
  Supports 785 (88.7) 285 (91.3) 500 (87.3)
  Objection 100 (11.3) 27 (8.7) 73 (12.7)
Physical activity, n (%) 33.355 < 0.001
  Low 295 (33.3) 70 (22.4) 225 (39.3)
  Middle 295 (33.3) 105 (33.7) 190 (33.2)
  High 295 (33.3) 137 (43.9) 158 (27.6)
Height/cm, ${\bar x}$±s 164.38±8.04 171.78±6.23 160.34±5.71 -20.429 < 0.001
Weight/kg, ${\bar x}$±s 65.67±13.09 75.99±12.90 60.04±9.20 -17.349 < 0.001
BMI/(kg/m2), ${\bar x}$±s 24.19±3.78 25.71±3.87 23.37±3.47 -9.014 < 0.001
Total body fat rate/%, ${\bar x}$±s 28.01±7.06 24.37±6.75 29.99±6.41 -12.240 < 0.001
Total skeletal muscle rate/%, ${\bar x}$±s 39.73±4.22 42.74±3.82 38.10±3.47 18.356 < 0.001
Depression score, ${\bar x}$±s 5.16±3.99 4.44±3.98 5.54±3.95 -4.450 < 0.001

Table 2

Association of total body fat rate and total skeletal muscle rate with depression in the assisted reproduction population"

Variable Total (n=885)
β (95%CI)a P valuea β (95%CI)b P valueb
BF%
  Q1 (≤24.50), M=21.40 0 0
  Q2 (24.51-31.20), M=28.10 0.93 (0.29, 1.57) 0.004 1.30 (0.35, 2.25) 0.007
  Q3 (>31.21), M=34.70 1.24 (0.61, 0.88) < 0.001 0.82 (0.11, 1.54) 0.025
  Ptrend < 0.001
  BF% (continuous variable) 0.06 (0.02, 0.10) 0.002 0.07 (0.01, 0.14) 0.040
SM%
  Q1 (≤37.68), M=35.66 0 0
  Q2 (37.69-41.46), M=39.53 -0.13 (-0.77, 0.51) 0.688 -0.14 (-0.87, 0.59) 0.712
  Q3 (>41.47), M=43.89 -1.33 (-1.97, -0.69) < 0.001 -1.16 (-2.12, -0.20) 0.018
  Ptrend < 0.001
  SM% (continuous variable) -0.12 (-0.18, -0.06) < 0.001 -0.12 (-0.24, -0.01) 0.029

Figure 1

Dose-response relationship between total body fat rate and total skeletal muscle rate with depression in the assisted reproduction population All models added variables such as age, gender, education, annual income, type of marriage, cause of infertility, family' s perception of performing ART, height, weight, BMI, and physical activity. BF%, total body fat rate; SM%, total skeletal muscle rate; ART, assisted reproductive technology; BMI, body mass index."

Table 3

Association of total body fat rate and total skeletal muscle rate with depression in an assisted reproduction population stratified by age and gender"

Variable Gender
Male (n=312) Female (n=573)
β (95%CI) P value β (95%CI) P valuea
BF%
  Q1 (≤24.50), M=21.40 0 0
  Q2 (24.51-31.20), M=28.10 1.26 (0.12, 2.40) 0.030 0.28 (-0.63, 1.20) 0.544
  Q3 (>31.21), M=34.70 2.05 (0.37, 3.72) 0.017 0.67 (-0.50, 1.83) 0.263
  Ptrend 0.020 0.136
  BF% (continuous variable) 0.08 (-0.03, 0.19) 0.144 0.05 (-0.04, 0.14) 0.302
SM%
  Q1 (≤37.68), M=35.66 0 0
  Q2 (37.69-41.46), M=39.53 0.87 (-0.90, 2.64) 0.332 -0.21 (-1.01, 0.60) 0.617
  Q3 (>41.47), M=43.89 -0.62 (-2.55, 1.31) 0.529 -0.67 (-1.83, 0.50) 0.262
  Ptrend 0.092 0.072
  SM% (continuous variable) -0.14 (-0.31, 0.04) 0.120 -0.09 (-0.23, 0.06) 0.249
Variable Age
≤30 years old (n=444) >30 years old (n=441)
β (95%CI) P value β (95%CI) P value
BF%
  Q1 (≤24.50), M=21.40 0 0
  Q2 (24.51-31.20), M=28.10 0.42 (-0.59, 1.44) 0.280 1.19 (0.18, 2.19) 0.008
  Q3 (>31.21), M=34.70 0.73 (-0.59, 2.05) 0.146 1.83 (0.48, 3.19) 0.020
  Ptrend < 0.001 0.089
  BF% (continuous variable) 0.02 (-0.08, 0.11) 0.764 0.12 (0.02, 0.22) 0.018
SM%
  Q1 (≤37.68), M=35.66 0 0
  Q2 (37.69-41.46), M=39.53 0.15 (-0.81, 1.11) 0.764 -0.61 (-1.71, 0.49) 0.270
  Q3 (>41.47), M=43.89 -0.66 (-1.98, 0.66) 0.326 -1.74 (-3.13, -0.34) 0.015
  Ptrend < 0.001 0.066
  SM% (continuous variable) -0.03 (-0.18, 0.13) 0.684 -0.19 (-0.35, -0.03) 0.013

Figure 2

Dose-response relationship between total body fat rate and total skeletal muscle rate with depression in assisted reproduction population of different gender and age All models added variables such as education, annual income, type of marriage, cause of infertility, family' s perception of line ART, height, weight, BMI, and physical activity. BF%, total body fat rate; SM%, total skeletal muscle rate; ART, assisted reproductive technology; BMI, body mass index."

1
McCarron RM , Shapiro B , Rawles J , et al. Depression[J]. Ann Intern Med, 2021, 174 (5): ITC65-ITC80.
2
Namdar A , Naghizadeh MM , Zamani M , et al. Quality of life and general health of infertile women[J]. Health Qual Life Outcomes, 2017, 15 (1): 139.

doi: 10.1186/s12955-017-0712-y
3
周飞京. 不孕不育夫妇生育相关压力和生活质量的相关性研究[D]. 郑州: 郑州大学, 2016.
4
El Kissi Y , Romdhane AB , Hidar S , et al. General psychopatho-logy, anxiety, depression and self-esteem in couples undergoing infertility treatment: A comparative study between men and women[J]. Eur J Obstet Gynecol Reprod Biol, 2013, 167 (2): 185- 189.

doi: 10.1016/j.ejogrb.2012.12.014
5
Zhang L , Shao H , Huo M , et al. Prevalence and associated risk factors for anxiety and depression in infertile couples of ART treatment: A cross-sectional study[J]. BMC Psychiatry, 2022, 22 (1): 616.

doi: 10.1186/s12888-022-04256-9
6
郑宇航. 接受辅助生殖技术治疗夫妇焦虑抑郁情绪及其影响因素[D]. 昆明: 昆明医科大学, 2021.
7
Luppino FS , de Wit LM , Bouvy PF , et al. Overweight, obesity, and depression: A systematic review and meta-analysis of longitudinal studies[J]. Arch Gen Psychiatry, 2010, 67 (3): 220- 229.

doi: 10.1001/archgenpsychiatry.2010.2
8
Favarato D . Obesity, body fat content and cardiovascular outcome: Beyond body mass index[J]. Arq Bras Cardiol, 2021, 116 (5): 887- 888.

doi: 10.36660/abc.20210074
9
Freigang R , Geier AK , Schmid GL , et al. Misclassification of self-reported body mass index categories[J]. Dtsch Arztebl Int, 2020, 117 (15): 253- 260.
10
Böhm A , Heitmann BL . The use of bioelectrical impedance analysis for body composition in epidemiological studies[J]. Eur J Clin Nutr, 2013, 67 (Suppl 1): S79- S85.
11
Cheng KY , Chow SK , Hung VW , et al. Diagnosis of sarcopenia by evaluating skeletal muscle mass by adjusted bioimpedance analysis validated with dual-energy X-ray absorptiometry[J]. J Cachexia Sarcopenia Muscle, 2021, 12 (6): 2163- 2173.

doi: 10.1002/jcsm.12825
12
Milaneschi Y , Simmons WK , van Rossum EFC , et al. Depression and obesity: Evidence of shared biological mechanisms[J]. Mol Psychiatry, 2019, 24 (1): 18- 33.

doi: 10.1038/s41380-018-0017-5
13
袁雯, 张奕, 陈力, 等. 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.

doi: 10.19723/j.issn.1671-167X.2023.03.007
14
李美玲. 安徽地区体力活动问卷的信度与效度研究[D]. 合肥: 安徽医科大学, 2023.
15
栾培培, 肖苏妹, 谷朝臣, 等. 生物电阻抗法测量体脂成分应用分析研究[J]. 中国实用内科杂志, 2017, 37 (1): 51- 53.
16
Kroenke K . PHQ-9: Global uptake of a depression scale[J]. World Psychiatry, 2021, 20 (1): 135- 136.

doi: 10.1002/wps.20821
17
Raef B , Ferdousi R . A review of machine learning approaches in assisted reproductive technologies[J]. Acta Inform Med, 2019, 27 (3): 205- 211.

doi: 10.5455/aim.2019.27.205-211
18
Toftager M , Bogstad J , Lossl K , et al. Cumulative live birth rates after one ART cycle including all subsequent frozen-thaw cycles in 1050 women: Secondary outcome of an RCT comparing GnRH-antagonist and GnRH-agonist protocols[J]. Hum Reprod, 2017, 32 (3): 556- 567.
19
Liu YF , Fu Z , Chen SW , et al. The analysis of anxiety and depression in different stages of in vitro fertilization-embryo transfer in couples in China[J]. Neuropsychiatr Dis Treat, 2021, 17, 649- 657.

doi: 10.2147/NDT.S287198
20
沈蕊, 杨丽, 王立聪, 等. 基于倾向评分匹配法的辅助生殖妊娠抑郁发生情况研究[J]. 中国妇幼健康研究, 2022, 33 (8): 104- 110.
21
尤蔚蔚. 体脂率与PCOS患者焦虑、抑郁状况的相关性研究[D]. 乌鲁木齐: 新疆医科大学, 2022.
22
Goossens GH . The metabolic phenotype in obesity: Fat mass, body fat distribution, and adipose tissue function[J]. Obes Facts, 2017, 10 (3): 207- 215.

doi: 10.1159/000471488
23
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
24
Zhang J , Lam SP , Li SX , et al. A community-based study on the association between insomnia and hypothalamic-pituitary-adrena-laxis: Sex and pubertal influences[J]. J Clin Endocrinol Metab, 2014, 99 (6): 2277- 2287.

doi: 10.1210/jc.2013-3728
25
Köhler CA , Freitas TH , Maes M , et al. Peripheral cytokine and chemokine alterations in depression: A meta-analysis of 82 studies[J]. Acta Psychiatr Scand, 2017, 135 (5): 373- 387.

doi: 10.1111/acps.12698
26
Cui H , Xiong Y , Wang C , et al. The relationship between BMI and depression: A cross-sectional study[J]. Front Psychiatry, 2024, 15, 1410782.

doi: 10.3389/fpsyt.2024.1410782
27
Liao W , Luo Z , Hou Y , et al. Age and gender specific association between obesity and depressive symptoms: A large-scale cross-sectional study[J]. BMC Public Health, 2020, 20 (1): 1565.

doi: 10.1186/s12889-020-09664-8
28
冯秋燕. 大学生身体意象及其与抑郁、社交回避苦恼关系研究[D]. 太原: 山西大学, 2005.
29
杨华, 李占博. 中老年人肌肉力量与抑郁风险研究[J]. 现代预防医学, 2024, 51 (9): 1684- 1688.
30
Jin Y , Kang S , Kang H . Individual and synergistic relationships of low muscle mass and low muscle function with depressive symptoms in Korean older adults[J]. Int J Environ Res Public Health, 2021, 18 (19): 10129.

doi: 10.3390/ijerph181910129
31
甘迎春, 钟小燕. 大学生抑郁症治疗中运动干预的作用研究[J]. 中国全科医学, 2023, 26 (27): 3466- 3467.
32
Fábrega-Cuadros R , Cruz-Díaz D , Martínez-Amat A , et al. Associations of sleep and depression with obesity and sarcopenia in middle-aged and older adults[J]. Maturitas, 2020, 142, 1- 7.
33
Agudelo LZ , Femenía T , Orhan F , et al. Skeletal muscle PGC-1α1 modulates kynurenine metabolism and mediates resilience to stress-induced depression[J]. Cell, 2014, 159 (1): 33- 45.

doi: 10.1016/j.cell.2014.07.051
34
Byeon CH , Kang KY , Kang SH , et al. Sarcopenia is not asso-ciated with depression in Korean adults: Results from the 2010-2011 Korean national health and nutrition examination survey[J]. Korean J Fam Med, 2016, 37 (1): 37- 43.

doi: 10.4082/kjfm.2016.37.1.37
35
Pearce M , Garcia L , Abbas A , et al. Association between physical activity and risk of depression: A systematic review and meta-analysis[J]. JAMA Psychiatry, 2022, 79 (6): 550- 559.

doi: 10.1001/jamapsychiatry.2022.0609
36
Zhao G , Ford ES , Dhingra S , et al. Depression and anxiety among US adults: Associations with body mass index[J]. Int J Obes (Lond), 2009, 33 (2): 257- 266.

doi: 10.1038/ijo.2008.268
37
Hsu YH , Liang CK , Chou MY , et al. Association of cognitive impairment, depressive symptoms and sarcopenia among healthy older men in the veterans retirement community in southern Taiwan: A cross-sectional study[J]. Geriatr Gerontol Int, 2014, 14 (S85): 102- 108.
38
Beyer I , Mets T , Bautmans I . Chronic low-grade inflammation and age-related sarcopenia[J]. Curr Opin Clin Nutr Metab Care, 2012, 15 (1): 12- 22.
39
Ershler WB , Keller ET . Age-associated increased interleukin-6 gene expression, late-life diseases, and frailty[J]. Annu Rev Med, 2000, 51, 245- 270.

doi: 10.1146/annurev.med.51.1.245
40
Ho RCM , Niti M , Kua EH , et al. Body mass index, waist circumference, waist-hip ratio and depressive symptoms in Chinese elderly: A population-based study[J]. Int J Geriatr Psychiatry, 2008, 23 (4): 401- 408.

doi: 10.1002/gps.1893
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