Huang GP, Mai LP, Zheng ZJ, Wang XP, He GD. Sex differences in the association between the muscle quality index and the incidence of depression: A cross-sectional study. World J Psychiatry 2024; 14(9): 1335-1345 [PMID: 39319235 DOI: 10.5498/wjp.v14.i9.1335]
Corresponding Author of This Article
Guo-Dong He, PhD, Technologist-in-charge, Institute of Medical Research, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No. 106 Zhongshan 2nd Road, Guangzhou 510080, Guangdong Province, China. heguodong@gdph.org.cn
Research Domain of This Article
Psychology, Clinical
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Gui-Ping Huang, Li-Ping Mai, Zhi-Jie Zheng, Xi-Pei Wang, Guo-Dong He, Institute of Medical Research, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, Guangdong Province, China
Co-corresponding authors: Xi-Pei Wang and Guo-Dong He.
Author contributions: Huang GP and Mai LP contributed equally to this work; Huang GP contributed to the writing - review & editing; Mai LP participated in the conceptualization and data curation of this manuscript; Huang GP, Mai LP, and Wang XP contributed to the formal analysis; Huang GP, Zheng ZJ, and He GD wrote the original draft; Zheng ZJ, Wang XP, and He GD participated in the methodology and software; Zheng ZJ and He GD were responsible for the project administration and resources; He GD contributed to the supervision of this manuscript. Wang XP and He GD were equal to this paper. All authors have read and approve the final manuscript.
Supported byGuangdong Medical Science and Technology Research Fund, No. A2023005.
Institutional review board statement: All National Health and Nutrition Examination Survey procedures and protocols have been reviewed and approved by the National Center for Health Statistics Research Ethics Review Board.
Informed consent statement: National Health and Nutrition Examination Survey is approved by the National Center for Health Statistics Research Ethics Review Board, and all participants provide informed consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The datasets (supplementary material) generated and analyzed during the current study are available from the National Health and Nutrition Examination Survey repository, https://www.cdc.gov/nchs/nhanes/index.htm.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Guo-Dong He, PhD, Technologist-in-charge, Institute of Medical Research, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, No. 106 Zhongshan 2nd Road, Guangzhou 510080, Guangdong Province, China. heguodong@gdph.org.cn
Received: July 7, 2024 Revised: July 16, 2024 Accepted: August 8, 2024 Published online: September 19, 2024 Processing time: 66 Days and 2.6 Hours
Abstract
BACKGROUND
Depression presents significant challenges to mental health care. Although physical activity is highly beneficial to mental and physical health, relatively few studies have conducted on the relationship between them.
AIM
To investigate the association between muscle quality index (MQI) and incidence of depression.
METHODS
The data used in this cross-sectional study were obtained from the 2011-2014 National Health and Nutritional Examination Survey, which included information on MQI, depression, and confounding factors. Multivariable logistic regression models were employed, while taking into account the complex multi-stage sampling design. A restricted cubic spline model was utilized to investigate the non-linear relationship between the MQI and depression. Additionally, subgroup analyses were performed to identify influential factors.
RESULTS
The prevalence of depression in this population was 8.44%. With the adjusted model, the MQI was associated with depression in females (odds ratio = 0.68, 95% confidence interval: 0.49-0.95) but not in males (odds ratio = 1.08, 95% confidence interval: 0.77-1.52). Restricted cubic spline adjustment of all covariates showed a significant negative non-linear relationship between depression and the MQI in females. The observed trend indicated an 80% decrease in the risk of depression for each unit increase in MQI, until a value of 2.2. Subsequently, when the MQI exceeded 2.2, the prevalence of depression increased by 20% for every unit increase in the MQI. Subgroup analyses further confirmed that the MQI was negatively associated with depression.
CONCLUSION
The MQI was inversely correlated with depression in females but not males, suggesting that females with a higher MQI might decrease the risk of depression.
Core Tip: Early monitoring of psychosocial disorders is crucial for mental health care. Muscle quality index (MQI) is a promising indicator of physical health, fitness, and mental well-being. While there is no conclusive evidence to establish a direct link between MQI and depression. In this study, a large-scale and representative sample of the American population revealed that sex differences existed in the association between the MQI and depression. Females with a higher MQI might exhibit a decreased likelihood of developing symptoms of depression and it might potentially serve as a safeguard against the onset of depression in females.
Citation: Huang GP, Mai LP, Zheng ZJ, Wang XP, He GD. Sex differences in the association between the muscle quality index and the incidence of depression: A cross-sectional study. World J Psychiatry 2024; 14(9): 1335-1345
Muscle quality index (MQI) is a measure of muscle quality, calculated as a strength index derived from the timed sit-to-stand test, body mass, and leg length, which represents the ratio of muscular strength to muscle mass[1]. The MQI is used to describe muscle strength, body composition, aerobic capacity, and obesity[1,2], and it is reportedly predictive of overall health, muscle atrophy, disability, and psychosocial disorders[3]. Multiple studies have indicated that a reduction in muscle mass contributes to musculoskeletal damage in older individuals and an increased risk of age-related muscular dystrophy[4]. The MQI is generally lower for females than males, which might be related to metabolism, hormone levels, and training[5]. Therefore, the MQI could potentially serve as a vital clinical and practical indicator to identify individuals at risk for physical disabilities.
Depression is a common psychological and mental disorder characterized by a marked and persistent depressed mood, accompanied by a loss of interest and motivation, which significantly impact quality of life. The prevalence of depression has continued to increase yearly and is currently the third leading contributor to the global burden of disease, which is projected to become the top cause by 2030, similar to the health risk of type 2 diabetes, and creates challenges to work performance, educational achievement, and social interactions[6,7].
Depression has been linked to various genetic, physiological, psychosocial, and environmental factors[8]. The complexity of depression poses a considerable challenge to traditional pharmacological- and psychotherapy-based treatment methods. The guidelines of the National Institute for Health and Clinical Excellence recommend a holistic approach for treatment of diseases, which involves the use of medications and psychological and physical therapies, along with various other interventions, to promote early recovery. Importantly, accumulating evidence suggests that physical activity and exercise can help to prevent depression. Effective treatment for depression for different age groups based on sex has received increasing attention. Notably, females are at a greater risk for moderate to severe depression[6,9].
Relatively few studies have investigated the correlation between MQI and depression to improve quality of life in large populations. Therefore, the aim of the present study was to evaluate the possible sex-related link between MQI and depression in American adults by analyzing data from the National Health and Nutrition Examination Survey (NHANES).
MATERIALS AND METHODS
Study approval and patient consent
The study protocol was approved by the Institutional Review Board of the National Center for Health Statistics and conducted in accordance with the ethical principles for medical research involving human subjects described in the Declaration of Helsinki. Prior to inclusion in this study, written informed consent was obtained from all subjects.
Study population and design
Data from the 2011-2014 cycle of the NHANES, an ongoing program managed by the National Center for Health Statistics under the Centers for Disease Control and Prevention, were employed in the current investigation. The reason for choosing the period from 2011 to 2014 was determined by the exclusive availability of the MQI test during the 2011-2012 and 2013-2014 cycles.
The data of 19931 participants were retrieved from the NHANES database. The study cohort included 4880 participants after excluding individuals aged < 18 years (n = 7954) and < 60 years (n = 3632), as well as those with incomplete data on the depression questionnaire (n = 1217), MQI test (n = 1392), and other covariates (n = 856). A flowchart of the selection process is provided in Figure 1.
Figure 1 Study cohort.
NHANES: National Health and Nutrition Examination Survey.
Measurement methods
In this study, the independent variable was MQI. The quantification involved calculating the proportion of the total arm and appendicular skeletal muscle (ASM) mass divided by the combined handgrip strength (HGS) of both the dominant and non-dominant hands. HGS was measured with a dynamometer (TKK 5401; Takei Scientific Instruments Co., Ltd., Tokyo, Japan), while ASM was assessed by dual-energy X-ray absorptiometry (DXA). Further information regarding the examination procedure can be found elsewhere[5]. To determine the ASM mass, the lean soft tissue of all four limbs was assessed by body composition analysis performed with DXA. Further information on the DXA methodology can be found in the NHANES data documentation files, while relevant indices are described in a previous report[10].
Depressive symptoms served as the dependent variable in this research. Assessments were conducted using the Patient Health Questionnaire-9 (PHQ-9), a screening tool consisting of nine items that inquired about the frequency of depressive symptoms encountered over the past 2 weeks[11]. The total score of the PHQ-9 ranged from 0 to 27, with scores of 0 to 9 indicating the absence of depression. In accordance with prior studies, a cutoff score of 10 was employed to identify clinically significant depression[12].
Covariate assessment
Assessment of covariates encompassed comprehensive evaluation of sociodemographic and lifestyle factors. The sociodemographic factors included age, sex, ethnicity, education level, marital status, poverty status, and body mass index (BMI). Interviews were conducted to obtain demographic information on age, sex, ethnicity (non-Hispanic white, non-Hispanic black, Mexican American, and others), education level (less than high school, high school, and college or more), and marital status (single, married, divorced, or widowed). Poverty was operationally defined as an income ratio of ≤ 1.0[13]. The categorization of family poverty income ratio was established as ≤ 1.00 and > 1.00. BMI was calculated as weight in kilograms divided by height in meters squared. The subjects were grouped based on BMI < 25 or ≥ 25. Diagnoses of diabetes, hypertension, hyperlipidemia, cardiovascular disease, and cancer were confirmed by medical professionals or self-reported by the participants. Lifestyle factors included smoking and recreational activities. Data pertaining to smoking status were obtained with the use of a questionnaire. Self-reported levels of recreational physical activity were categorized as none, moderate, or vigorous.
Statistical analysis
In accordance with the NHANES analytical guidelines, appropriate weighting, stratification, and clustering procedures were implemented due to the complex multi-stage sampling design. Starting from 2002, NHANES weights were computed biennially. The data collected from 2011 to 2014 encompassed two consecutive 2-year sampling cycles. The adjusted weights were calculated as (1/2) × WTMEC2YR11-12 combined with (1/2) × WTMEC2YR13-14, with WTMEC2YRs representing variables obtained from the NHANES 2011-2014 data.
Continuous variables are reported as the mean and standard error and categorical variables as the percentage (%). The Student’s t-test and χ2 test were used to assess differences in baseline variables between groups. Logistic regression analysis was used to identify a potential correlation between the MQI and depression. Three logistic regression models were used: Model 1, model 2 (modified to account for age, sex, race, marital status, and education level), and model 3 (modified to account for smoking, diabetes mellitus, high blood pressure, high cholesterol levels, cardiovascular disease, cancer, BMI, participation in leisure activities, and poverty income ratio). Additionally, the linearity of the associations was assessed utilizing a generalized additive model incorporating a restricted cubic splines function. If a non-linear correlation was found, a two-segment linear regression model was utilized to precisely fit each interval and establish the threshold effect. All statistical analyses were conducted using the software packages EmpowerStats (www.empowerstats.com) and R (https://www.r-project.org/). A probability P value < 0.05 was considered statistically significant.
RESULTS
Baseline characteristics
The baseline characteristics of the 4880 participants, including 412 (8.44%) diagnosed with depression, are shown in Table 1. The occurrence of depression was higher in males than females. The MQI (mean = 3.38) was significantly lower in females than males. Approximately half (48.4%) of the study participants were females. The proportions of the study participants who identified as non-Hispanic White, non-Hispanic Black, Mexican American, and others were 40.84%, 21.66%, 11.91%, and 25.59%, respectively. More than half (62.44%) of the study participants attained a level of education that extended to college or beyond. Nearly half of the participants were married and 24.16% were smokers. Most (75.29%) of the high-income study participants were females. There were no significant differences in the incidence of hypertension, diabetes, and cardiovascular disease between males and females. More than half (61.00%) of the study participants were diagnosed with hyperlipidemia, while relatively few (3.93%) were diagnosed with cancer. The majority of both females (66.44%) and males (68.26%) were overweight (BMI ≥ 25).
Table 1 Demographic and clinical characteristics according to gender.
Comparisons of the study variables based on sex are shown in Table 2. For all participants, the MQI was negatively associated with depression in model 1 and model 2. In contrast to males, the MQI was negatively associated with the risk of depression in females, as confirmed by all three models. Model 1 showed that the risk of depression was decreased with an increase in the MQI [odds ratio (OR) = 0.59, 95% confidence interval (CI): 0.42-0.81, P = 0.0035]. Model 2 showed that the correlation between the MQI and depression remained after adjusting for age, race, marital status, and education level (OR = 0.55, 95%CI: 0.38-0.80, P = 0.0035). Model 3 revealed that the MQI and depression were inversely associated (OR = 0.68, 95%CI: 0.49-0.95, P = 0.0482) (Table 2).
Table 2 Weighted logistic regression analysis of muscle quality index with depression.
Restricted cubic spline adjustment of all covariates revealed a non-linear association between the MQI and depression in females. Notably, a higher MQI was inversely associated with a lower risk of depression (Figure 2). A two-piecewise linear regression model revealed a threshold effect of all adjusted covariates. As shown in Table 3, a non-linear association occurred at an inflection point of 2.2. Until MQI reached 2.2, there was a notable correlation between every unit increase in MQI and decrease in the risk of depression of 80% (95%CI: 0.1-0.6, P = 0.0008). Subsequently, when the MQI exceeded 2.2, the prevalence of depression increased by 20% for every unit increase in the MQI (95%CI: 0.6-1.0, P = 0.086), although there was no statistically significant association.
The results of subgroup analyses of all covariates to explore the potential association between the MQI and depression are presented in the form of a forest plot. There was a consistent and stable negative association between the prevalence of depression and MQI levels in all subgroups, except for an education level less than high school, vigorous recreation activities, and diabetes. As shown in Figure 3, the MQI was inversely associated with the risk of depression in the subgroups of age < 45 years, education level of college and above, moderate recreational activity, poverty income ratio > 1, BMI < 25, former smoker, cardiovascular disease, cancer, non-hypertension, and non-diabetes. Overall, these results remained unchanged by logistic regression analysis with the same general subgroups.
Figure 3 Forest plots of subgroup analyses.
Age, race, married, education level, recreation activity, poverty income ratio, body mass index, smoking, hypertension, hyperlipidemia, diabetes, cardiovascular disease and cancer were all adjusted except the variable itself. CI: Confidence interval.
DISCUSSION
With the increased incidence of depression, it is imperative to encourage physical activity and exercise, which have therapeutic effects on mild to moderate depression and can reduce mortality and symptoms of severe depression[14,15]. Although relatively few prospective studies have explored the correlation with depression, the MQI is a promising indicator of physical health, fitness, and mental well-being[16-18]. While there is no conclusive evidence to establish a direct link between preserving muscle mass and strength and the prevention of mental disorders like depression, a comparable outcome was observed in adolescents, who exhibited an inverse relationship between the MQI and psychosocial factors, such as depression, anxiety, stress, and cardiometabolic risk[19]. Although the sample size was limited, it provided significant implications for the potential relationship between MQI and depression in adolescents. In this study, a large-scale and representative sample of the American population from the NHANES 2011-2014 database was used to examine the relationship between the MQI and depression. A survey of 4880 participants revealed a notable inverse non-linear relationship between the MQI and depression was observed in females, while no significant correlation was found in males.
Early identification and monitoring of psychosocial disorders is crucial in all demographic groups, especially teenagers and females. Puberty occurs about 2 years earlier in females than males, similar to sex differences in the incidence of depression, suggesting a link to hormonal changes, rather than age, which persist throughout the reproductive years of females[20-22]. Further, the viewpoint that females are more prone to depression is consistent with the findings of the present study (Table 1), which found a higher incidence of depression in females than males (11.38% vs 5.68%, respectively). Previous studies have primarily focused on age-related decreases in hand grip strength associated with muscle loss[23]. In fact, depression in females is reportedly influenced by varying eating patterns and specific nutritional needs during different stages of life[24].
In females younger than 45 years, greater HGS was associated with a higher MQI and reduced risk of depression[25,26]. Subgroup analysis based on race and marital status of females confirmed an inverse relationship between the MQI and depression. Moreover, an education level below high school and engaging in vigorous physical activity were associated with a slightly higher risk of depression, although differences with other subgroups were not statistically significant. Depression is a morbidity of diabetes and two-fold more common in diabetics than the general population[27,28]. The results of the present study found that diabetes could result in decreased muscle volume, which is linked to a greater risk of depression. However, further investigations are needed to confirm this correlation.
Interestingly, a robust negative correlation was observed between the MQI and depression with moderate recreational activity as a covariate (OR = 0.49, 95%CI: 0.33-0.72). Several studies have shown that physical exercise and activity confer protective effects on mental health and reduce symptoms of depression[29]. Physical exercise and activity can maintain and even increase muscle mass, while promoting the release of neurotransmitters, such as dopamine, which can improve mood and reduce feelings of depression. The findings of the present indicate that moderate recreational activities can improve muscle strength, as demonstrated by the significant correlation between the MQI and depression in the subgroup engaged in moderate recreational activities. Individuals with a poverty income ratio > 1 (OR = 0.60, 95%CI: 0.43-0.83) and a higher MQI tended to be more actively involved in social and daily living activities. Moreover, a higher MQI was associated with a greater likelihood to engage in social and daily living activities, which can reduce the risk of depression, while improving the happiness index and increasing discretionary income, which positively influences mental well-being. On the other hand, a poverty income ratio of ≤ 1 (OR = 0.90, 95%CI: 0.57-1.43) was associated with poorer quality of life and feelings of social isolation, which can cause social pressure and difficulties, ultimately resulting in decreased muscle mass and a greater risk of depression. A perceived inequality in socioeconomic status might influence mental health. Analysis of a subset of smokers found that smoking cessation (OR = 0.37, 95%CI: 0.20-0.70) coupled with a high MQI was associated with a reduced risk of depression, attributable to alterations to physiology, neurotransmitters, and mental well-being, which might impact the emergence of depressive symptoms[30]. Subgroup analysis found body dissatisfaction was more prevalent in overweight females (BMI ≥ 25) (OR = 0.87, 95%CI: 0.49-1.56) than men who experienced negative life events, such as bullying and low self-esteem, which can cause stress and increase the risk of depressive symptoms[31,32]. Cancer patients (OR = 0.32, 95%CI: 0.13-0.80) often experience loss of muscle mass, especially during treatment[33,34]. Likewise, numerous investigations have established that cancer patients frequently experience intense physical pain, exhaustion, reduced appetite, and discomfort caused by treatment, which have been linked to symptoms of depression. Increasing muscle mass is beneficial for recovery of physical function and health, while reducing anxiety, sadness, and the risk of depression.
Limitations
There were some limitations to this study that should be addressed. First, the study primarily relied on the subjective self-reported PHQ-9 questionnaire to assess depression, rather than an objective measurement. Second, there is currently no consensus on the most accurate measure of MQI, as the optimal approach might differ based on available resources, level of sensitivity, and potential applications[2]. Third, the cross-sectional design of this study could have constrained the establishment of a causal correlation between the MQI and depression. Nonetheless, additional prospective studies are needed to substantiate these findings. In spite of these limitations, this study generated significant and captivating results as a foundation for future research.
Future directions
Females with a higher MQI might exhibit a decreased likelihood of developing symptoms of depression. The MQI could potentially serve as a safeguard against the onset of depression in females. Further investigations are needed to validate this correlation and elucidate the underlying mechanisms.
CONCLUSION
The MQI was not associated with the prevalence of depression in males. However, a notable inverse non-linear relationship between the MQI and depression was observed in females, suggesting that a higher MQI could potentially have a positive impact on the prevention of depression.
ACKNOWLEDGEMENTS
Thanks to the National Health and Nutritional Examination Survey. We would like to express our sincere thanks to all the participants in this study.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Psychiatry
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade B
Novelty: Grade B
Creativity or Innovation: Grade B
Scientific Significance: Grade B
P-Reviewer: Roever L S-Editor: Wang JJ L-Editor: A P-Editor: Zhao YQ
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