Incidence of sarcopenic obesity in older patients with diabetes and association between sarcopenic obesity and higher-level functional capacity: evaluation based on a consensus statement

Abstract

We used a consensus statement to diagnose sarcopenic obesity, evaluated incidence of sarcopenic obesity in older patients with diabetes, and examined whether sarcopenic obesity was associated with their higher-level functional capacity. Outpatients with diabetes (age, ≥65 years) undergoing treatment at Ise Red Cross Hospital were included. The Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC)—a self-administered questionnaire—was used to assess their higher-level functional capacity. Sarcopenic obesity was evaluated based on the consensus statement diagnostic criteria—i.e., presence or absence of decreased skeletal muscle mass was evaluated based on appendicular skeletal muscle mass/body weight and obesity was assessed based on body fat mass percentage. To calculate the adjusted β coefficient of sarcopenic obesity for higher-level functional capacity, multiple regression analyses were performed using TMIG-IC scores as the dependent variable and four categories (non-sarcopenia/non-obesity was used as a reference) that included sarcopenia and obesity as the predictor and moderator variables. Among the 310 patients included, the sarcopenic obesity incidence was 13.1% and 14.2% in men and women, respectively. When the non-sarcopenia/non-obesity group was used as a reference, the adjusted β coefficient of sarcopenic obesity for scores of the TMIG-IC was –2.09 (p = 0.014) in men. However, the women showed no relationship between sarcopenic obesity and TMIG-IC scores. In older men with diabetes, sarcopenic obesity was associated with a decline in higher-level functional capacity.

AGE OF PATIENTS with diabetes continues to grow with the growing population of older adults [1]. The incidence of reduced activities of daily living (ADL) is high in older patients with diabetes [2]. Lawton et al. [3] described the degree of complexity required for functioning in daily tasks in elderly individuals. His hierarchical model with seven conceptual levels includes life maintenance, followed by the successively more complex levels of functional health, perception-cognition, physical self-maintenance, instrumental self-maintenance, effectance, and social role. ADL includes basic ADL (BADL), instrumental ADL (IADL), which involves complex tasks, and higher-level functional capacity, which involves intellectual activities and social roles. Of these ADLs, a decrease in higher-level functional capacity is observed first [3] and associated with cognitive decline, increased medical costs, and deaths [4-6]. Therefore, higher-level functional capacity in older patients with diabetes is a clinically important outcome.

Factors associated with deterioration of higher-level functional capacity in older patients with diabetes include aging, complications, hyperglycemia, drugs, and depression [7-9], as well as obesity and loss of skeletal muscle mass [10, 11]. Changes in body composition caused by aging and disease are associated with loss of skeletal muscle mass and increased body fat mass [12, 13]. Sarcopenia is considered a disease characterized by skeletal muscle mass reduction, muscle weakness, and physical function, deterioration and has recently been recognized as a new complication in older patients with diabetes. Meanwhile, a previous study has shown that body fat mass percentage is remarkably higher in older patients with diabetes than in those without diabetes. Sarcopenia [10, 14] and increased body fat mass percentage [11, 15] are associated with decreased ADL and increased mortality. Thus, sarcopenia and increased body fat mass percentage (i.e., obesity) are clinically important issues in older patients with diabetes.

Recently, increasing emphasis has been placed on sarcopenic obesity, which is a condition defined as the presence of both sarcopenia and obesity [16, 17]. Some studies previously reported that sarcopenic obesity was closely associated with decreased ADL [18, 19]; however, another report revealed no association between these two factors [20], both of which involved community-dwelling elderly people. A main reason for such inconsistent results is differences in the definitions of sarcopenic obesity depending on the study.

With this background, a consensus statement [21] for sarcopenic obesity has been released in Europe. To the best of our knowledge, this was the first study to evaluate the relationship between sarcopenic obesity and higher-level functional capacity using the consensus statement [21] in older patients with diabetes. Since older patients with diabetes have many complications and are at risk for decreased ADL, we hypothesized that sarcopenic obesity in such patients was closely associated with decreased higher-level functional capacity. The purpose of this study was to verify the incidence of sarcopenic obesity based on the consensus statement in older patients with diabetes, and to verify its association with their higher-level functional capacity.

Materials and Methods

Study design and subjects

In this cross-sectional study, we included outpatients with diabetes (age, ≥65 years) who were undergoing treatment between July 2020 and July 2021 at Ise Red Cross Hospital, Ise City, Mie Prefecture. This study was approved by the Ethics Board of Ise Red Cross Hospital, and all patients provided written informed consent. Patients with alcohol addiction, severe psychiatric disorders, a history of malignant tumor diagnosis, or inability to cooperate with the study independently were excluded from the investigation.

Evaluation of higher-level functional capacity

The Tokyo Metropolitan Institute of Gerontology Index of Competence (TMIG-IC), a self-administered questionnaire, was used to assess higher-level functional capacity [22]. This questionnaire is widely used in Japan to evaluate higher-level functional capacity, and its reliability and validity have been determined. It consists of 13 items. Specifically, five questions relate to IADL (e.g., meal preparation, financial management, and the use of transportation), four questions relate to intellectual activities, and four questions relate to social roles. TMIG-IC uses two-multiple choice questions with Yes/No options. The score varies from 0 to 13 points, with a higher score indicating better higher-level functional capacity.

Evaluation of sarcopenic obesity

Sarcopenic obesity was evaluated based on the diagnostic criteria of the consensus statement [21], which was recently published. Grip strength was measured using a Smedley grip dynamometer (Grip-D, Takei Scientific Instruments Co., Ltd., Japan) and the mean maximum value of the right and left sides was calculated. Decreased muscle strength was defined as a grip strength of <28 kg for men and <18 kg for women [23]. The five-times-sit-to-stand test was used to assess physical function. Patients requiring ≥12 seconds to complete the test, which was measured with a stopwatch, were defined as those with decreased physical function. Multi-frequency bioelectrical impedance analysis (Seca medical body composition analyzers 525, GmbH & Co., Hamburg, Germany) was used to examine skeletal muscle mass and body fat mass percentage. Decreased skeletal muscle mass was defined as skeletal muscle mass weight divided by body weight (SMW/W), of <31.5% for men and <22.1% for women. Among patients who experienced decreased skeletal muscle mass, those who experienced reduced grip strength or physical function were diagnosed with sarcopenia. Obesity was defined as a body fat mass percentage of ≥29% for men and ≥41% for women. The patients were divided into the following four groups: non-sarcopenia/non-obesity, sarcopenia alone, obesity alone, and sarcopenic obesity.

Measurement of other variables

The following factors were evaluated: age, sex, body mass index (BMI) (weight [kg]/height [m²]), smoking habits, drinking habits, classification of diabetes (type 1 or type 2), duration of diabetes, Hemoglobin A1c (HbA1c), hypertension, dyslipidemia, diabetic retinopathy, diabetic nephropathy, depression, living alone, social isolation, and use of antidiabetic agents. Classification of diabetes into type 1, type 2, and others was performed according to the diagnostic criteria of the Japan Diabetes Society [24]. Systolic and diastolic blood pressures were measured in the physician’s office and hypertension was defined as systolic blood pressure of ≥130 mmHg, diastolic blood pressure of ≥80 mmHg, or consumption of oral antihypertensive medication, whichever was met. For lipids, dyslipidemia was defined as either a triglycerides (TG) ≥150 mg/dL, high-density lipoprotein-cholesterol (HDLC) <40 mg/dL, low-density lipoprotein-cholesterol (LDLC) ≥120 mg/dL (LDLC ≥100 mg/dL for patients with coronary artery disease), or consumption of oral lipid-lowering drugs. The presence or absence of diabetic retinopathy was determined based on a diagnosis by an ophthalmologist. Diabetic nephropathy was defined as a urinary albumin/urinary creatinine ratio ≥30 mg/g Cre. Cardiovascular disease was determined to be present when the patient had either a current or a medical history of ischemic heart disease such as angina pectoris or myocardial infarction or cerebrovascular diseases such as cerebral infarction. To evaluate depression, we used a nine-item questionnaire (the Japanese version of the Patient Health Questionnaire 9 [J-PHQ-9]), which was developed by Muramatsu et al. [25] and has been validated. It is a four-point scale questionnaire (almost every day: 3 points; more than half the days; 2 points; several days; 1 point; not at all; 0 points) related to the symptoms in the past 2 weeks. The total score ranges from 0 to 27 points, and a higher score indicate a greater degree of depression. To examine social isolation, the patients were instructed to answer the question regarding face-to-face interaction (“How often do you see someone or go out with someone, including your family who do not live with you, your friends, or your neighbors?”) and non-face-to-face contact (“How often do you communicate with your family who do not live with you, your friends, or your neighbors by telephone or letters?”). They were asked to answer either by “less than once a week” or “at least once a week.” Social isolation was defined as an answer of “less than once a week” to both questions [8].

Statistical analyses

The patients were classified into non-sarcopenia/non-obesity, sarcopenia alone, obesity alone, and sarcopenic obesity groups and their characteristics by sex are shown. The analysis of variance was used for continuous variables and the chi-square test was used for binary variables for group comparisons. To calculate the adjusted partial regression coefficient of sarcopenic obesity for higher-level functional capacity, multiple regression analyses were performed using scores of the TMIG-IC as the dependent variable and the abovementioned four categories (non-sarcopenia/non-obesity was used as a reference) as the predictor and moderator variables. Based on previous studies [14, 18-20] and clinical judgment, the following factors were adjusted: age, HbA1c, duration of diabetes, the number of complications (hypertension, dyslipidemia, diabetic retinopathy, diabetic neuropathy, diabetic nephropathy, and cardiovascular disease), eGFR, depression, living alone, social isolation, and antidiabetic agent use. Furthermore, as a sensitivity analysis, a univariate analysis was performed using the scores of the TMIG-IC as the dependent variable and each variable as the predictor variable. Then, multivariate analysis was performed using statistically significant variables from the univariate analysis. The two-sided significance level was set at <0.05%. Analyses were performed using STATA version 16.0 (Stata Corporation LP, College Station, TX).

Results

A total of 310 patients (191 men and 119 women) were included in the analysis. The patient characteristics have been presented in Tables 1 and 2. Among the men, 103 (53.9%), 16 (8.4%), 47 (24.6%), and 25 patients (13.1%) were classified into the non-sarcopenia/non-obesity, sarcopenia alone, obesity alone, and sarcopenic obesity groups, respectively. Among the women, 67 (56.3%), 9 (7.6%), 26 (21.9%), and 17 patients (14.2%) were divided into the non-sarcopenia/non-obesity, sarcopenia alone, obesity alone, and sarcopenic obesity groups, respectively. The incidence of hypertension and dyslipidemia was higher, and the TMIG-IC score was lower in the sarcopenic obesity group than in the other groups in men. In contrast, no intergroup difference for the TMIG-IC score was found in women.

Table 1 Characteristics of the analysis population in men

	Non-sarcopenia/ Non-obesity n = 103 (53.9%)	Sarcopenia alone n = 16 (8.4%)	Obesity alone n = 47 (24.6%)	Sarcopenic obesity n = 25 (13.1%)	p value
Age (years), mean (SD)	75.3 (7.3)	77.7 (6.1)	74.8 (5.7)	75.4 (4.5)	0.494
BMI (kg/m2), mean (SD)	22.5 (2.5)	21.4 (3.1)	27.0 (2.8)	25.3 (2.0)	<0.001*
T1DM/T2DM, %	10.8/89.2	6.2/93.8	2.1/97.9	8.0/92.0	0.639
HbA1c (%), mean (SD)	7.2 (0.9)	7.1 (1.1)	7.6 (1.2)	7.6 (1.0)	0.123
Duration of diabetes (years), mean (SD)	17.3 (11.3)	23.3 (7.3)	20.3 (11.3)	19.4 (10.0)	0.176
Alcohol consumption, %	23.3	18.7	27.6	40.0	0.331
Smoking, %	33.0	50.0	25.5	40.0	0.286
Hypertension, %	70.2	68.7	89.3	100.0	0.002*
Dyslipidemia, %	67.6	50.0	78.7	84.0	0.044*
Retinopathy, %	35.9	50.0	38.2	36.0	0.751
Neuropathy, %	33.0	43.7	40.4	36.0	0.750
Nephropathy, %	50.4	50.0	61.7	68.0	0.313
eGFR (mL/min/1.73 m2), mean (SD)	60.4 (22.3)	50.0 (26.4)	58.0 (19.0)	57.3 (20.8)	0.424
Cardiovascular disease, %	21.2	53.3	22.7	24.0	0.074
SMW/W (%), mean (SD)	37.0 (4.4)	29.5 (1.2)	32.0 (3.0)	27.9 (2.1)	<0.001*
Grip strength (kg), mean (SD)	29.7 (6.3)	24.1 (5.0)	30.4 (6.6)	24.0 (7.8)	<0.001*
5T-CST (s), mean (SD)	9.2 (1.8)	11.3 (3.3)	8.9 (1.7)	12.1 (2.9)	<0.001*
PHQ-9 score (point), mean (SD)	2.8 (4.2)	4.3 (4.8)	3.3 (4.7)	3.3 (4.4)	0.745
Living alone, %	15.0	6.6	13.3	25.0	0.432
Social isolation, %	22.6	35.7	15.0	27.2	0.395
Oral hypoglycemic agents, %	71.5	62.5	85.1	72.0	0.458
Insulin, %	57.8	75.0	67.3	80.0	0.136
TMIG-IC (points), mean (SD)	11.5 (1.8)	11.8 (1.5)	11.0 (2.5)	10.3 (2.8)	0.002*

SD, standard deviation; BMI, body mass index; T1DM/T2DM, type 1/type 2 diabetes mellitus; HbA1c, hemoglobin A1c; eGFR, estimated glomerular filtration rate; SMW/W, skeletal muscle mass weight divided by body weight; 5T-CST, 5 time-chair stand test; PHQ-9, Patient Health Questionnaire-9; TMIG-IC, Tokyo Metropolitan Institute of Gerontology Index of Competence; *p < 0.05

Table 2 Characteristics of the analysis population in women

	Non-sarcopenia/ Non-obesity n = 67 (56.3%)	Sarcopenia alone n = 9 (7.6%)	Obesity alone n = 26 (21.9%)	Sarcopenic obesity n = 17 (14.2%)	p value
Age (years), mean (SD)	76.7 (5.6)	76.0 (8.2)	74.2 (5.3)	75.7 (4.1)	0.309
BMI (kg/m2), mean (SD)	22.5 (3.2)	21.2 (2.8)	27.7 (4.9)	25.7 (4.4)	<0.001*
T1DM/T2DM, %	13.6/86.4	44.4/55.6	0/100	5.8/94.2	0.027*
HbA1c (%), mean (SD)	7.5 (1.3)	7.5 (1.0)	7.7 (0.6)	7.3 (1.0)	0.812
Duration of diabetes (years), mean (SD)	18.8 (10.8)	23.7 (12.5)	18.1 (9.1)	22.2 (8.2)	0.359
Alcohol consumption, %	4.4	0	7.6	5.8	0.818
Smoking, %	4.4	0	11.5	0	0.294
Hypertension, %	73.1	55.5	84.6	82.3	0.290
Dyslipidemia, %	65.6	66.6	84.6	88.2	0.124
Retinopathy, %	41.7	44.4	42.3	41.1	0.999
Neuropathy, %	43.2	44.4	34.6	58.8	0.483
Nephropathy, %	41.7	44.4	65.3	52.9	0.225
eGFR (mL/min/1.73 m2), mean (SD)	60.8 (24.1)	52.5 (26.5)	64.0 (21.9)	51.9 (20.7)	0.297
Cardiovascular disease, %	15.3	25.0	20.8	31.2	0.574
SMW/W (%), mean (SD)	28.9 (5.5)	19.8 (3.0)	23.9 (3.4)	19.7 (1.4)	<0.001*
Grip strength (kg), mean (SD)	19.5 (4.4)	15.4 (3.8)	18.0 (3.7)	16.3 (3.0)	0.004*
5T-CST (s), mean (SD)	10.5 (2.1)	10.6 (2.9)	10.1 (2.2)	11.2 (1.1)	0.685
PHQ-9 score (point), mean (SD)	3.4 (3.7)	3.3 (3.6)	4.5 (4.5)	4.2 (5.4)	0.779
Living alone, %	18.7	11.1	16.0	18.7	0.945
Social isolation, %	6.0	33.3	13.0	13.3	0.118
Oral hypoglycemic agents, %	76.1	55.5	88.4	88.2	0.133
Insulin, %	68.6	66.6	73.0	88.2	0.432
TMIG-IC (points), mean (SD)	11.5 (2.0)	9.5 (1.9)	12.0 (3.5)	11.4 (1.6)	0.067

SD, standard deviation; BMI, body mass index; T1DM/T2DM, type 1/type 2 diabetes mellitus; HbA1c, hemoglobin A1c; eGFR, estimated glomerular filtration rate; SMW/W, skeletal muscle mass weight divided by body weight; 5T-CST, 5 time-chair stand test; PHQ-9, Patient Health Questionnaire-9; TMIG-IC, Tokyo Metropolitan Institute of Gerontology Index of Competence; *p < 0.05

Table 3 shows results of multiple regression analyses. When the non-sarcopenia/non-obesity group was used as a reference, the adjusted β coefficient for TMIG-IC scores in the sarcopenia alone, obesity alone, and sarcopenic obesity groups was 0.112 (p = 0.172), –0.034 (p = 0.674), and –0.209 (p = 0.014), respectively, in men, as well as –0.128 (p = 0.313), 0.055 (p = 0.661), and 0.084 (p = 0.500), respectively, in women.

Table 3 Multiple regression with higher-level functional capacity as the outcome

	Unadjusted		Adjusted
	β	p	β	p	R2
Men					0.448
Age, per year increase			–0.305	<0.001*
HbA1c, per 1% increase			–0.209	0.019*
Duration of diabetes, per year increase			–0.057	0.483
Numbers of comorbidity, per 1 increase			0.005	0.951
eGFR, per 1 mL/min/1.73 m2 increase			–0.052	0.563
PHQ-9 score, per 1 point increase			–0.390	<0.001*
Living alone (vs. no)			–0.058	0.489
Social isolation (vs. no)			–0.204	0.014*
Oral hypoglycemic agents (vs. no)			0.133	0.129
Insulin (vs. no)			–0.047	0.569
Non-sarcopenia/Non-obesity	Ref	Ref	Ref	Ref
Sarcopenia alone	0.040	0.586	0.112	0.172
Obesity alone	–0.095	0.206	–0.034	0.674
Sarcopenic obesity	–0.187	0.012*	–0.209	0.014*
Women					0.305
Age, per year increase			–0.038	0.776
HbA1c, per 1% increase			0.157	0.301
Duration of diabetes, per year increase			–0.196	0.167
eGFR, per 1 mL/min/1.73 m2 increase			–0.172	0.290
Numbers of comorbidity, per 1 increase			–0.128	0.454
PHQ-9 score, per 1 point increase			–0.153	0.248
Living alone (vs. no)			0.186	0.142
Social isolation (vs. no)			–0.240	0.070
Oral hypoglycemic agents (vs. no)			0.169	0.237
Insulin (vs. no)			0.020	0.884
Non-sarcopenia/Non-obesity	Ref	Ref	Ref	Ref
Sarcopenia alone	–0.215	0.022*	–0.128	0.313
Obesity alone	0.088	0.349	0.055	0.661
Sarcopenic obesity	–0.011	0.901	0.084	0.500

β, standardized regression coefficient; R², coefficient of determination; HbA1c, hemoglobin A1c; eGFR, estimated glomerular filtration rate; PHQ-9, Patient Health Questionnaire-9; TMIG-IC, Tokyo Metropolitan Institute of Gerontology Index of Competence; *p < 0.05

The sensitivity analysis revealed that significant variables were age, PHQ-9, social isolation, and insulin in men and age, duration of diabetes, and social isolation in the univariate analysis in women. Results of the multivariate analysis using these variables are shown in Table 4. When the non-sarcopenia/non-obesity group was used as a reference, the adjusted β coefficient for TMIG-IC scores in the sarcopenia alone, obesity alone, and sarcopenic obesity groups was 0.117 (p = 0.133), –0.088 (p = 0.264), and –0.233 (p = 0.004), respectively, in men, and –0.158 (p = 0.134), 0.059 (p = 0.568), and –0.024 (p = 0.809), respectively, in women.

Table 4 Sensitivity analysis

	Univariate analysis		Multivariate analysis
	β	p	β	p	R2
Men					0.381
Age, per year increase	–0.159	0.028*	–0.273	0.001*
PHQ-9 score, per 1 point increase	–0.364	<0.001*	–0.416	<0.001*
Social isolation (vs. no)	–0.198	0.015*	–0.158	0.041*
Insulin (vs. no)	–0.148	0.041*	–0.120	0.117
Non-sarcopenia/Non-obesity	Ref	Ref	Ref	Ref
Sarcopenia alone	0.040	0.586	0.117	0.133
Obesity alone	–0.095	0.206	–0.088	0.264
Sarcopenic obesity	–0.187	0.012*	–0.233	0.004*
Women					0.230
Age, per year increase	–0.200	0.028*	–0.098	0.325
Duration of diabetes, per year increase	–0.188	0.048*	–0.167	0.097
Social isolation (vs. no)	–0.347	<0.001*	–0.297	0.004*
Non-sarcopenia/Non-obesity	Ref	Ref	Ref	Ref
Sarcopenia alone	–0.215	0.022*	–0.158	0.134
Obesity alone	0.088	0.349	0.059	0.568
Sarcopenic obesity	–0.011	0.901	–0.024	0.809

HbA1c, hemoglobin A1c; PHQ-9, Patient Health Questionnaire-9; β, standardized regression coefficient; R², coefficient of determination; *p < 0.05

Discussion

Results of the present study showed that the proportion of sarcopenic obesity, which was determined based on the consensus statement, was 13.1% for men and 14.2% for women. Sarcopenic obesity was associated with decreased higher-level functional capacity in men. To the best of our knowledge, this was the first study to evaluate the relationship between sarcopenic obesity and higher-level functional capacity in older patients with diabetes using the consensus statement.

The rate of sarcopenic obesity differs from study to study. Studies involving community-dwelling older adults showed that it was 5.8% [18] and 8% [20]. Studies involving patients with diabetes indicated that it was 7.4% for men and 9% for women [26], but another study demonstrated that it was 2.7% [27]. As compared with these previous studies, the proportion of sarcopenic obesity was higher in the present study that involved older patients with diabetes. We suspect the following to be possible causes for this. First, in these previous studies, sarcopenia was diagnosed based on the formula: skeletal muscle index (SMI) divided by the square of the height (hSMI) [20, 26, 27]. However, the present study employed the following formula in accordance with the consensus statement: SMI divided by weight (wSMI). According to a previous study that employed hSMI and wSMI for evaluating sarcopenic obesity and compared the results between the two [28], the prevalence of sarcopenic obesity in patients with high BMI is higher when wSMI was used. This may explain the reason for higher incidence of sarcopenic obesity in the present study. To identify many patients with sarcopenic obesity, hSMI are used for lean patients (BMI ≤22 kg/m²) and wSMI for obese patients (BMI ≥25 kg/m²). In fact, the mean BMI in the sarcopenic obesity group in the present study was ≥25 kg/m², suggesting that wSMI is suitable for identifying patients with sarcopenic obesity. Second, we suspect the effect of hyperglycemia and age. The incidence of sarcopenia is higher in diabetic patients than in non-diabetic patients [29]. Oxidative stress due to hyperglycemia and muscle atrophy and decreased muscle function attributable to inflammation may lead to sarcopenia [16, 17]. Therefore, the proportion of sarcopenic obesity was higher in the present study that involved diabetic patients than in the previous studies that included community-dwelling older adults. In terms of age, the mean age of the present study was higher than that of a study of diabetic patients by Kim et al. [26], of which the mean age was the 50s. Given that the present study included older patients, the incidence of sarcopenic obesity may be high. Third, differences in the definition of obesity may have come into play. In studies involving community-dwelling older adults, obesity was defined based on body fat mass percentage and its incidence was 32%–38% [18, 20]. According to a study of diabetic patients by Takahashi et al. [28] in which obesity was defined as a BMI ≥25 kg/m², the proportion of obesity was 35%, but that of sarcopenic obesity was low at 2.7%. Changes in body composition associated with aging include decreased muscle mass and increased body fat mass percentage [12, 13]. This may result in the limited sensitivity of BMI for detecting obesity. In other words, when obesity is defined based on BMI, sarcopenic obesity may be underrepresented in patients with sarcopenia who experience decreased muscle mass. Taken together, the higher incidence of sarcopenic obesity in the present study may be explained by the following: this was a study involving patients with diabetes, wSMI was used for evaluating sarcopenia, and the definition of obesity differed between the present study and the previous studies.

Association between sarcopenic obesity and ADL remains controversial. Although some previous studies reported that sarcopenic obesity was associated with decreased ADL [18, 19], another report showed no association between these two factors [20], both of which involving community-dwelling older adults. Results of the present study on older patients with diabetes revealed a significant association between sarcopenic obesity and decreased higher-level functional capacity. This suggested that the impact of sarcopenic obesity on decreased ADL may be huge in older patients with diabetes when compared with the general elderly population. Logistic analysis of this study showed that a β for sarcopenic obesity was higher than that for age, HbA1c, depression, and social isolation in men. These results suggest that, when considering the risk for decreased ADL, it is extremely important to call attention to sarcopenic obesity, in addition to age, HbA1c, depression, and social isolation. On the other hand, there was no significant relationship between sarcopenic obesity and decreased higher-level functional capacity in women in the present study. While women have higher body fat percentages than men, they have lower abdominal visceral fat amount, which has been associated with insulin resistance, inflammation, oxidative stress, and decreased skeletal muscle mass [30]. The visceral fat amount is lower and the body fat mass percentage is higher in women than in men. Therefore, the percentage of patients with visceral fat obesity is higher in male patients with sarcopenic obesity, whereas the rate is lower in female patients with sarcopenic obesity (many female patients with excessive subcutaneous fat may be included). These factors may explain the reason why we did not find a relationship between sarcopenic obesity and decreased higher-level functional capacity in women.

This study could not elucidate the mechanism for the association between sarcopenic obesity and decreased higher-level functional capacity; however, we suspect the following to be possible causes. First, insulin resistance, oxidative stress, and inflammation may be involved. Previous studies have suggested that both sarcopenia and obesity are associated with the onset of insulin resistance and inflammation [30]. Sarcopenia and obesity promote one another and synergistically increase inflammation and insulin resistance [30]. As a result, muscle mass and muscle performance decrease, possibly resulting in decreased ADL. The proportion of hypertension and dyslipidemia, which are associated with insulin resistance, was higher in the sarcopenic obesity group in men. Therefore, the presence of insulin resistance may explain the relationship between sarcopenic obesity and decreased higher-level functional capacity in older patients with diabetes. Second, a decrease in testosterone levels may be involved. Testosterone plays an important role in sustaining skeletal muscle mass and muscle performance; however, testosterone levels decrease in patients with sarcopenia or obesity [30]. A further study is required for elucidating the mechanism for the association between sarcopenic obesity and decreased higher-level functional capacity.

In terms of clinical findings, this study may aid in the early detection of risk factors for decreased higher-level functional capacity in older male patients with diabetes with sarcopenia, which is diagnosed based on the consensus statement. Outcomes of this study suggest that it is important to focus on sarcopenic obesity, in addition to age, complications, depression, and social isolation, which are identified as factors contributing to decreased ADL in previous studies. This study has several limitations. First, the patients were outpatients at a clinic specializing in diabetes; thus, patients with comparatively severe diabetes may be overrepresented. Therefore, the results of this study should be applied to patients with stable glucose levels or diabetes managed by a family physician with due caution. Second, sample size was relatively small. A further study including more cases will be needed. Third, no analysis was performed on data on cognitive function or educational history, which may affect the results. Finally, as this was a cross-sectional study, it was difficult to make statements regarding causality. A longitudinal study will be required in the future for examining the association between sarcopenic obesity and decreased higher-level functional capacity in older patients with diabetes.

Despite the limitations noted above, this study indicates that the proportion of sarcopenic obesity, which was determined based on the consensus statement, is 13.1% for men and 14.2% for women in older patients with diabetes. Furthermore, sarcopenic obesity is associated with decreased higher-level functional capacity in older male patients with diabetes. This study suggests that it is important to be aware of the possibility of decreased higher-level functional capacity in older patients with diabetes if they have sarcopenia.

Acknowledgments

The authors would like to thank the staff members of the Department of Metabolic Diseases at the Ise Red Cross Hospital for their cooperation in this study. This study received no funding.

Disclosure

None of the authors have any potential conflicts of interest associated with this research.

Ethical Standards

This study was approved by the Ethical Review Board of the Ise Red Cross Hospital and conducted in accordance with the Helsinki Declaration. Written informed consent was obtained from all participants before enrolment.

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