ORIGINAL ARTICLE

Year : 2022  |  Volume : 36  |  Issue : 1  |  Page : 19-24

Obesity, sarcopenia, and depressive symptoms in patients with alzheimer's disease

Yu- San Chang M.D., Ph.D ¹, Chiu- Hsiang Wu R.N., M.S ², Chin- Jen Wang M.D., M.S ³, Hsin- Ning Lee M.D., M.S ³, Yu- Hsuan Wu M.D., M.S ^3
1 Department of Psychiatry, Catholic Mercy Hospital, Catholic Mercy Medical Foundation, Hukou Township, Hsinchu County, Taiwan
² Department of Nursing, Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan
³ Department of Neuropsychiatry, Kaohsiung Municipal Kai-Syuan Psychiatric Hospital, Kaohsiung, Taiwan

Correspondence Address:
Yu- San Chang
No.29, Zhongxiao Road, Hukou Township, Hsinchu County 303
Taiwan

Source of Support: None, Conflict of Interest: None

2

DOI: 10.4103/TPSY.TPSY_3_22

Objective: In this study, we intended to study the association between depressive symptoms and the status of sarcopenia or obesity in patients with mild-to-moderate Alzheimer's disease (AD). Methods: We enrolled 176 outpatients aged 65 to 89 years with mild-to-moderate AD. The study participants were divided into four groups according to the presence or absence of sarcopenia and obesity. We analyzed differences among the four groups and used multiple logistic regression to examine associations with depressive symptoms. Results: Most of the patients were obese without sarcopenia (n [%] = 94 [53.5%]). The patients with sarcopenia either with or without obesity were significantly more male, compared to those without sarcopenia (p < 0.001). The obese patients either with or without sarcopenia tended to be significantly older (p < 0.01), and to have significantly higher prevalence of depressive symptoms (p < 0.05), and significantly more receiving antidepressant therapy (p < 0.05), compared to those in the nonobesity groups. After adjusting for covariates, we further found that the obese patients either with or without sarcopenia were significantly positively associated with depressive symptoms compared to the nonsarcopenia/nonobesity group (odds ratio [OR] [95% confidence interval (CI)] = 6.88 [1.11–42.71], p < 0.05; OR [95% CI] = 5.95 [1.82–19.43], p < 0.01), respectively, and those patients with sarcopenia without obesity did not have any significant depressive symptoms. Conclusion: Obesity could be a potential confounder for the association between sarcopenia and depressive symptoms in patients with AD. Future studies suggest that depression interventions using reducing adiposity or increasing muscle mass need to be considered.

Keywords: Alzheimer's disease, depressive symptoms, obesity, sarcopenia

Introduction

Methods

[3],[21],[22],[23], including serum levels of 25-hydroxyvitamin D, albumin, creatinine, and estimated glomerular filtration rate.

Definition of sarcopenia and obesity

Sarcopenia was defined as the presence of both low muscle function (low physical performance or low muscle strength) and low muscle mass [Figure 1] ^[1]. Skeletal muscle mass (kg) was measured, the lean tissue mass of the arms and legs by bioimpedance analysis (BIA) (IOI 353, Jawon, Seoul, Korea), and then converted into the skeletal muscle mass index (SMI) by dividing the height in meters squared (kg/m²). A low SMI was defined as less than 8.9 kg/m² in men and 6.4 kg/m² in women according to Taiwanese norms ^[24]. Low muscle strength was defined as handgrip strength less than 22.4 kg in men and 14.3 kg in women, adjusted according to Taiwanese norms ^[25],[26]. In the walking speed test, individuals were asked to walk over a six-meter straight course at their usual pace. A cutoff of less than 1 m/s identifies participants with low physical performance for both sexes ^[25].

The participants are classified as being obese if their percentage body fat measured by BIA ^[11] was in the highest quintile (cutoff values: 25% for men, 30% for women according to the Health Promotion Administration, Ministry of Health and Welfare in Taiwan). Based on the presence or absence of sarcopenia and obesity, the study participants were classified into four groups: sarcoma/obesity, nonsarcopenia/obesity, sarcopenia/nonobesity, and nonsarcopenia/nonobesity.

Statistical analysis

Differences among the four groups were analyzed using a one-way analysis of variance for continuous variables and the Chi-squared test for categorical variables. Scheffe's post hoc analysis was used for significant continuous variables. To evaluate the association with depressive symptoms, odds ratios with 95% confidence intervals for depressive symptoms were obtained by doing multiple logistic regression analysis while controlling for covariates. We selected covariates a priori based on their association with depression, sarcopenia, or obesity and added them to the model in a sequential manner. We first adjusted for age and sex (model 1), and then further adjusted for MMSE scores and years of education (model 2). In the final model, medical variables including the use of antidepressants and chronic comorbidity burden were added to the model (model 3).

We used Statistical Package for the Social Science software version 20.0 for Windows (SPSS Inc., Chicago, Illinois, USA) to analyze the study variables. The differences between the groups were considered significant if p-values were smaller than 0.05.

Results

The proportions of patients in the nonsarcopenia/nonobesity, sarcopenia/nonobesity, nonsarcopenia/obesity, as well as sarcoma and obesity groups were 13.6%, 13.6%, 53.5%, and 19.3%, respectively. [Table 1] summarizes the comparisons of demographic and clinical characteristics through sarcopenia and obesity status. The sarcopenia groups either with or without obesity were significantly most male (p < 0.001) compared to the nonsarcopenia groups. The obesity groups either with or without sarcopenia were significantly older (p < 0.01) compared to the nonsarcopenia/nonobesity group. The prevalences of depressive symptoms and use of antidepressants in the obesity groups either with or without sarcopenia were significantly higher than those in the nonobesity groups (p < 0.05 and p < 0.05), respectively.{Table 1}

Multiple logistic regression analysis adjusted for age and sex showed that both the nonsarcopenia/obesity and sarcoma/obesity groups had significant associated with depressive symptoms compared to the nonsarcopenia/nonobesity group (odds ratio [OR] [95% confidence interval (95% CI)] = 5.31 [1.76 - 16.07], p < 0.01 and OR [95% CI] = 5.02 (1.29 - 19.54), p < 0.05), respectively [Table 2], model 1). The significant associations between depressive symptoms and obesity groups either with or without sarcopenia were persisted after successively adjusting for MMSE scores and years of education (OR [95% CI] = 5.22 [1.73 - 15.77], p < 0.01 and OR [95% CI] = 5.05 [1.29 - 19.74], p < 0.05), respectively [Table 2], model 2), and comorbidity burden and use of antidepressants (OR [95% CI] = 5.95 (1.82 - 19.43), p < 0.01 and OR [95% CI] = 6.88 (1.11 - 42.71), p < 0.05), respectively [Table 2] model 3). But the sarcopenia/nonobesity group had no significant association with depressive symptoms compared to the nonsarcopenia/nonobesity group after consecutively adjusting covariates to the model.{Table 2}

Discussion

In the present study [Table 1], the patients with sarcopenia either with or without obesity were significantly more male compared to those without sarcopenia (p < 0.001). The obesity groups either with or without sarcopenia were significantly older (p < 0.01) and had significantly higher prevalences of depressive symptoms (p < 0.05) and the use of antidepressants (p < 0.05) compared to the nonobesity groups. We further found that the obese patients either with or without sarcopenia were still significantly associated with depressive symptoms (p < 0.05) compared to those neither sarcopenia nor obesity after successively adding covariates to the model. But the sarcopenia without obesity group was not significantly associated with depressive symptoms compared to those with neither sarcopenia nor obesity in all regression models. Our results suggest that obesity could be a potential confounder for the association between sarcopenia and depression in patients with AD.

Chien et al. ^[24] reported that the prevalence of sarcopenia in males is higher than in females (23.6% vs. 18.6%) in community-dwelling older adults in Taiwan ^[24], and a similar finding ^[27] has also been reported in Hong Kong (males 12.3% vs. females 7.6%). Our results are consistent with those studies in that the prevalence of sarcopenia either with or without obesity is higher in male than in female. But another study ^[3] has been reported no differences in the prevalence of sarcopenia between sexes in patients with cognitive decline.

Although the prevalence of obesity declines with age after 60 years of age, this finding does not imply that excess fat storage is uncommon in the elderly, as progressively more fat is stored in the abdominal cavity ^[12]. While most previous studies have focused on BMI-based general obesity, it does not differentiate muscle mass from fat in individuals. Individuals with a low BMI may still have as much fat as those with a high BMI, and a higher BMI may mean greater muscle mass in some individuals. Accordingly, BMI is not the best measure of adiposity. We used percentage body fat [Table 1] instead of BMI to determine obesity and found that the obesity groups either with or without sarcopenia were older significantly than the nonobesity groups (p < 0.01).

The prevalences of depression symptoms in the nonsarcopenia/nonobesity, sarcopenia/nonobesity, nonsarcopenia/obesity, and sarcoma/obesity groups were 29.2%, 37.5%, 59.6%, and 61.8%, respectively, in the study [Table 1]. Our results are much higher than those in Ishll et al.'s study ^[11] that they have found 8.5%, 11.0%, 11.6%, and 26% of patients having depressive symptoms, respectively, in community old adults according to sarcopenia and obesity status. Many studies have reported that both sarcopenia and obesity are associated with depression in the elderly, respectively ^[1],[5],[28]. Ishll et al. ^[11] reported that neither sarcopenia nor obesity alone is associated with depressive symptoms in Japanese old adults and that a synergistic impact is exerted through sarcoma and obesity on the risk of depressive symptoms. But most of the previous studies have included community-dwelling old adults, and the characteristics of the participants are different from our study. We found that obesity either with sarcoma (p < 0.05) or without sarcopenia (p < 0.01) was all significantly associated with depressive symptoms in patients with AD, but that those with sarcopenia without obesity were not associated with depressive symptoms [Table 2].

Although our results did not support the hypothesis that the co-existence of sarcopenia and obesity would be more associated with depressive symptoms compared with either alone, it seemed to indicate that obesity has more influence than sarcopenia on the odds of depressive symptoms in patients with AD. It is possible obesity could be a potential confounder for the association between sarcopenia and depression in patients with AD. Further investigating whether reduced adiposity or increased muscle mass, can be the interventions for depression symptoms in patients with AD.

The mechanism underlying the association between obesity and depressive symptoms in patients with dementia is unclear. But several theories have been proposed that could potentially explain the association between obesity, depressive symptoms, and dementia.

Several studies have reported that fat accumulation leads to higher concentrations of cytokines and lipid dysregulation, triggering muscle degradation and insulin resistance, which consequently contribute to cognitive dysfunction and depression ^{[29],[30],[31]}. In addition, inflammation due to obesity has been reported to be involved in hypothalamic–pituitary–adrenal axis dysregulation, which is well-known to be associated with depression and dementia ^[32],[33]. Future study is needed to establish the causal pathways and identify mediators of the association.

Study limitations

The readers are cautioned not to overinterpret the study results because our study had six limitations.

• The GDS-15 is a depression screening tool rather than a diagnostic instrument. Therefore, the association of depression and sarcopenia and obesity status might not be completely established. The self-rated scale assessment implies that depression symptoms may be affected by patients' cognitive function and education level.
• Vascular risk factors may be the shared etiology of dementia and depression. Obesity is an important factor of vascular pathologies. The diagnosis of AD-associated dementia was made according to the DSM-5. But most individuals have some levels of mixed pathology, we can include those other causes of dementia.
• The noradrenergic and specific serotonergic antidepressants have increased both appetite and body weight side effects which could be a cofounder of obesity.
• We excluded those who could not communicate or complete a walking test and those with severe hearing impairment or blindness. This may have caused underestimated prevalence of sarcopenia or obesity.
• The cross-sectional study design can limit the ability to establish a causal relationship among cognition, depressive symptoms, and obesity.
• The observed associations could be confounded through unmeasured or uncontrolled variables such as HbA1c, glucose, cholesterol, and triglycerides.

Study summary

We used percentage body fat instead of BMI-based values to determine obesity and found that obesity either with or without sarcopenia was associated with depressive symptoms in patients with AD in this study. Those with sarcopenia without obesity were not associated with depressive symptoms. Our results suggest that obesity could be a potential confounder for the association between sarcopenia and depression in patients with AD. Future studies on depression interventions symptoms using reducing adiposity or increasing muscle mass could be taken into consideration.

Acknowledgment

When this study was done, the author, YSC, was associated with Kaohsiung Municipal Kai-Syuan Psychiatric Hospital.

Financial Support and Sponsorship

This study received the funding from Kaohsiung Municipal Kai-Syuan Psychiatric Hospital.

[TAG:2]Conflicts of Interest[/TAG:2]

The authors declare the absence of any competing conflicts of interest in writing this article.



 

References

1.	Chen LK, Woo J, Assantachai P, et al.: Asian Working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc 2020; 21: 300-7.e2.
2.	Lee HN, Chang YS, Wu YH, et al.: Sarcopenia in female patients with Alzheimer's disease are more likely to have lower levels of haemoglobin and 25-hydroxyvitamin D. Psychogeriatrics 2020; 20: 858-64.
3.	Sugimoto T, Ono R, Murata S, et al.: Prevalence and associated factors of sarcopenia in elderly subjects with amnestic mild cognitive impairment or Alzheimer disease. Curr Alzheimer Res 2016; 13: 718-26.
4.	World Health Organization: Obesity and Overweight. Geneva, Switzerland: Word Health Organization, 2015.
5.	Xiang X, An R: Obesity and onset of depression among U.S. middle-aged and older adults. J Psychosom Res 2015; 78: 242-8.
6.	Jagielski AC, Brown A, Hosseini-Araghi M, et al.: The association between adiposity, mental wellbeing, and quality of life in extreme obesity. PLoS One 2014; 9: E92859.
7.	Rosenberg IR: Summary comments. Am J Clin Nutr 1989; 50: 1231-3.
8.	Lu CW, Yang KC, Chang HH, et al.: Sarcopenic obesity is closely associated with metabolic syndrome. Obes Res Clin Pract 2013; 7: e301-7.
9.	Batsis JA, Mackenzie TA, Barre LK, et al.: Sarcopenia, sarcopenic obesity and mortality in older adults: Results from the National Health and Nutrition Examination Survey III. Eur J Clin Nutr 2014; 68: 1001-7.
10.	Cho Y, Shin SY, Shin MJ: Sarcopenic obesity is associated with lower indicators of psychological health and quality of life in Koreans. Nutr Res 2015; 35: 384-92.
11.	Ishll S, Chang C, Tanaka T, et al.: The association between sarcopenia obesity and depressive symptoms in older Japanese adults. PLoS One 16; 11: E0162898.
12.	Seidell JC, Visscher TL: Body weight and weight change and their health implications for the elderly. Eur J Clin Nutr 2000; 54 (Suppl 3): S33-9.
13.	Hughes CP, Berg L, Danziger WL, et al.: A new clinical scale for the staging of dementia. Br J Psychiatry 1982; 140: 566-72.
14.	Liu HC, Lin KN, Teng EL, et al.: Prevalence and subtypes of dementia in Taiwan: a community survey of 5297 individuals. J Am Geriatr Soc 1995; 43: 144-9.
15.	Wang CY, Hua MS, Chiu MJ, et al.: The comparison between Mini-Mental State Examination (MMSE) and Clinical Dementia Rating scale (CDR) in evaluating patients with Alzheimer's disease. Taiwan J Psychiatry 2003; 17: 23-32.
16.	American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, 5th Edition) (DSM-5). Washington DC, USA: American Psychiatric Association, 2013.
17.	Lawton MP, Brody EM: Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 1969; 9: 179-86.
18.	Liang CK, Chen LK, Tsai CF, et al.: Screening depression among institutionalized older Chinese men by minimum data set: we need a new instrument. J Geriatr Psychiatry Neurol 2011; 24: 179-83.
19.	Sheikh JY, Yesavage JA: Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version. Clin Gerontol 1986; 5: 165-73.
20.	Liao CY, Yeh YZ, Ke HZ: Geriatric depression scale (GDS) – a preliminary report of reliability and validity for Chinese version. Changhua J Med 1995; 18: 11-7.
21.	Kim MK, Baek KH, Song KH, et al.: Vitamin D deficiency is associated with sarcopenia in older Koreans, regardless of obesity: The Fourth Korea National Health and Nutrition Examination Surveys (KNHANES IV) 2009. J Clin Endocrinol Metab 2011; 96: 3250-6.
22.	Visser M, Kritchevsky SB, Newman AB, et al.: Lower serum albumin concentration and change in muscle mass: the Health, Aging and Body Composition Study. Am J Clin Nutr 2005; 82: 531-7.
23.	Levey AS, Bosch JP, Lewis JB, et al.: a more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999; 130: 461-70.
24.	Chien MY, Huang TY, Wu YT: Prevalence of sarcopenia estimated using a bioelectrical impedance analysis prediction equation in community-dwelling elderly people in Taiwan. J Am Geriatr Soc 2008; 56: 1710-5.
25.	Liu LK, Lee WJ, Liu CL, et al.: Age-related skeletal muscle mass loss and physical performance in Taiwan: implications to diagnostic strategy of sarcopenia in Asia. Geriatr Gerontol Int 2013; 13: 964-71.
26.	Wu SW, Wu SF, Liang HW, et al.: Measuring factors affecting grip strength in a Taiwan Chinese population and a comparison with consolidated norms. Appl Ergon 2009; 40: 811-5.
27.	Lau EM, Lynn HS, Woo JW, et al.: Prevalence of and risk factors for sarcopenia in elderly Chinese men and women. J Gerontol A Biol Sci Med Sci 2005; 60: 213-6.
28.	Forman-Hoffman VL, Yankey JW, Hillis SL, et al.: Weight and depressive symptoms in older adults: direction of influence? J Gerontol B Psychol Sci Soc Sci 2007; 62: S43-51.
29.	Barzilay JI, Blaum C, Moore T, et al.: Insulin resistance and inflammation as precursors of frailty: the cardiovascular health study. Arch Intern Med 2007; 167: 635-41.
30.	Bremmer MA, Beekman AT, Deeg DJ, et al.: Inflammatory markers in late-life depression: results from a population-based study. J Affect Disord 2008; 106: 249-55.
31.	Levine ME, Crimmins EM: Sarcopenic obesity and cognitive functioning: the mediating roles of insulin resistance and inflammation? Curr Gerontol Geriatr Res 2012; 2012: 826398.
32.	Huang CW, Lui CC, Chang WN, et al.: Elevated basal cortisol level predicts lower hippocampal volume and cognitive decline in Alzheimer's disease. J Clin Neurosci 2009; 16: 1283-6.
33.	Ricci S, Fuso A, Ippoliti F, et al.: Stress-induced cytokines and neuronal dysfunction in Alzheimer's disease. J Alzheimers Dis 2012; 28: 11-24.

This article has been cited by 1 Resveratrol regulates inflammation and improves oxidative stress via Nrf2 signaling pathway: Therapeutic and biotechnological prospects Seyed Hossein Shahcheraghi, Fateme Salemi, Shlomo Small, Suliman Syed, Farzam Salari, Waqas Alam, Wai San Cheang, Luciano Saso, Haroon Khan Phytotherapy Research. 2023; [Pubmed] | [DOI]