Disability, Frailty and Depression in the Community-dwelling Elderly with Osteosarcopenia

DOI: https://doi.org/10.21203/rs.3.rs-27449/v1

Abstract

Background

The purpose of this study was to investigate the prevalence of osteosarcopenia in the over 60-year-old community and to evaluate whether osteosarcopenia is associated with disability, frailty and depression.

Methods

This study was performed using the baseline data of Namgaram-2, which was developed to study the relationship between the prevalence of musculoskeletal disorders and activity limitations in the elderly in rural areas. Among the 1010 surveyed subjects, 885 study subjects who were 60 years or older and had all necessary tests performed were selected. The Kaigo-Yobo checklist was completed for diagnosis of frailty and the degree of disability in everyday life was evaluated by WHODAS. To understand the symptoms of depression in the elderly, the Geriatric Depression Scale-Short Form-Korean (GDSSF-K) was used. The study subjects were divided into four groups: the normal group, in which both sarcopenia and osteopenia were undiagnosed, osteopenia only, sarcopenia only and the osteosarcopenia group, which was diagnosed with both sarcopenia and osteopenia.

Results

Of the 885 subjects over 60 years old evaluated, the normal group comprised 34.0%, the only osteopenia group 33.7%, the only sarcopenia group 13.1%, and the osteosarcopenia group 19.2%. WHODAS, Kaigo-Yobo, and GDSSF scores were statistically significantly higher in the osteosarcopenia group compared the other groups.

Conclusions

Osteosarcopenia is a relatively common disease group in the elderly community that may cause deterioration of health outcomes. Therefore, when evaluating osteopenia or sarcopenia in the elderly, management of those in both disease groups should occur together.

Background

As people live longer, the world's population is projected to age rapidly in most regions.[1] Korea became an aging society in 2018, and by 2026 Korea will become a super-aged society.[2] Elderly populations are increasing the prevalence of many chronic diseases, including osteoporosis and sarcopenia.[3]

Although osteoporosis-based clinical outcomes and treatment recommendation studies have been increasingly popular in recent decades, sarcopenia and related studies have been less frequent.[4] In addition, sarcopenia has recently been classified as M62.84 in the ICD-10-CM since 2016. [5]

Sarcopenia is most often seen in metabolic disorders such as diabetes mellitus, obesity, and other serious diseases, including congestive heart failure, chronic renal failure, and chronic obstructive pulmonary disease (COPD). [68] Sarcopenia is substantially correlated with osteopenia (or osteoporosis) in older populations. Several studies have shown that sarcopenia and osteopenia (osteosarcopenia, OS) share similar risk factors and biological pathways.[9] OS is associated with severe physical impairment, which presents a major threat to the loss of freedom in later life. The combination of these two conditions exacerbates adverse health effects and creates a significant problem for the elderly. This combination has been presented as a "hazardous duet" that adds the predisposition of falling from sarcopenia to bone weakness in those with osteopenia.[10]

In recent years, questionnaire research tools (WHODAS, Kaigo-Yobo) have been developed to define disability and frailty as health outcomes and to measure these outcomes easily and effectively.[11, 12] OS patients have a higher risk of fracture from falling than those with osteopenia and sarcopenia alone. Studies have also shown that sarcopenia acts as a major risk factor for frailty.[13] However, a study on the relationships among OS, disability and frailty is lacking.

Therefore, the purpose of this study was to investigate the prevalence of OS in the over 60-year-old community and to evaluate whether OS is associated with disability, frailty and depression.

Methods

Participants

This study was performed using the baseline data of Namgaram-2, which was developed to study the relationship between the prevalence of musculoskeletal disorders and activity limitations in the elderly in rural areas. Among the 1,010 surveyed subjects, 885 were 60 years or older and had all necessary tests performed. These 885 were selected as study subjects.

The cognitive performance evaluation for participants with no cognitive function disorders was performed via an interview study utilizing the Korean version of the Mini-Mental State Examination for Dementia Screening (MMSE-DS).[14] All surveys were evaluated by a medical professional. After providing written informed consent, participants completed a questionnaire to assess cognitive function. Subsequently, fasting blood samples were collected from participants, followed by physical function evaluation.

All investigations were conducted after obtaining participant consent and after being reviewed by the Institutional Review Board of our institution (approval number: GIRB-A16-0012).

Materials

Data on social demographic variables such as gender, age, marital status, economic level perceived by the person, and health behavior variable such as smoking was acquired. Also, survey results, such as one on whether or not the subject was affected by hypertension and diabetes, were used. In addition, the blood test measured hemoglobin, cholesterol, albumin, uric acid, γ-GTP, and creatinine.

1) Frailty (Kaigo-Yobo checklist in Korean elderly)

The Kaigo-Yobo checklist[15] was developed by researchers at the Tokyo Senior Research Institute, and the reliability and validity in Korean elderly people have been confirmed.[16] The checklist consists of 15 questions and is a survey instrument that focuses on social activities and evaluation of daily life. The Kaigo-Yobo checklist is a complex domain phenotype aging assessment tool and comprises questions only. The checklist’s 15 items consist of four products for nutritional status; three items for fall; two items for activities; two items for social relationships; and one item each for general health status, communication, mobility, and leisure activities. Furthermore, the appropriate answer to each query was 'Yes' or 'No,' and a score of one point was possible for each query. The final score is in the range of 0–15 points, and the higher the score was indicated the higher the degree of frailty.

2) WHODAS-12

The World Health Organization (WHO) developed the WHO Disability Assessment Schedule (WHODAS) based on the International Classification of Functioning, Disability, and Health (ICF). WHODAS-12 measures the difficulties caused by health conditions by dividing the difficulties into six areas (cognition, mobility, self-care, getting along, life activities, and participation).[17]

All questions were measured with a 5-point Likert item system (1 point, not very difficult to 5 points, very severe). The final score is in the range of 0-100 points, and the higher the score, the higher the degree of disability in everyday life.

3) Depressive symptoms

To understand the symptoms of depression in the elderly, the Geriatric Depression Scale-Short Form-Korean (GDSSF-K) adapted and developed for aged people in Korea was used.[18] The GDSSF-K has the advantage of comprising items that are easy for the elderly to understand relative to other current depression measurement tools. This scale of 15 items is graded from 0 to 15 points; higher values indicate worse depression.

4) Osteosarcopenia

Although several criteria have been proposed to define sarcopenia, the recent criteria of the Asian Working Group for Sarcopenia (AWGS 2019) were applied in this study. [19]

Dual energy X-ray absorptiometry (DEXA) was used to measure muscle mass. In addition, the measured total appendicular skeletal muscle mass (ASM), excluding bone and fat, divided by the square of the height (m2) was calculated (ASM/Ht2) and used as the skeletal muscle mass index (SMI). Sarcopenia was defined as SMI less than 7.0 kg/m2 in men and less than 5.4 kg/m2 in women. Muscle strength was evaluated by grip strength, and the measurement was conducted using the Smedley-type dynamometer (TKK 5401; Takei Scientific Instruments Co., Tokyo, Japan). Both hands were evaluated, twice each. Grip strength was used for analysis as one of the four measured values. The maximum value was used as a reference level, for men below 28 kg and for women below 18 kg.

Osteopenia was measured using data from dual energy X-ray absorptiometry (DEXA) and osteopenia was diagnosed when the T-score was less than − 1.0.

The study subjects were divided into four groups[20]: the normal group, in which both sarcopenia and osteopenia were undiagnosed, and the osteosarcopenia group, which was subdivided into those diagnosed with both sarcopenia and osteopenia, osteopenia only, and sarcopenia only.

Statistical analysis

The general characteristics of the participants generated descriptive statistics; the chi-square test was conducted on categorical variables, and the ANOVA test was performed on continuous variables. Post-hoc analysis was performed using the turkey method.

The comparison of WHODAS, Kaigo-Yobo, and GDSSF values ​​among the four groups of study subjects occurred after adjustment for gender, age, marital status, economic level, smoking status, hypertension, diabetes, hemoglobin, uric acid, albumin, r-GTP, creatinine, and cholesterol. The SPSS 25.0 program (IBM SPSS Inc., Chicago, IL, USA) was used as the analysis tool, and the significance level was set to 0.05.

Result

General characteristics

Of the 885 elderly people over 60 years old evaluated, 594 (67.1%) were women. The average participant age was 70.3 ± 6.2 years, 561 (63.4%) participants had spouses, and 577 (69.7%) had a higher than average economic status. The smoking rate was 7.5%, 447 (50.5%) were diagnosed with hypertension, and 192 (21.7%) were diagnosed with diabetes.

The diagnosis of osteopenia and osteoporosis (below T-score – 1.0) occurred in 468 subjects (47.1%), and sarcopenia was diagnosed in 286 (32.3%) (Table 1).

Table 1

General characteristics (Total number = 885)

Variables

 

Number

%

Sex

Male

291

32.9%

 

Female

594

67.1%

Age (years)

mean ± SD

70.3

6.2

Spouse

Yes

561

63.4%

 

No

324

36.6%

Economic status

Low

268

30.3%

 

Middle

465

52.5%

 

High

152

17.2%

Smoking

Non-smoker

819

92.5%

 

Smoker

66

7.5%

Hypertension

No

438

49.5%

 

Yes

447

50.5%

Diabetes mellitus

No

693

78.3%

 

Yes

192

21.7%

Osteopenia

No

417

47.1%

 

Yes

468

52.9%

Sarcopenia

No

599

67.7%

 

Yes

286

32.3%

Hb (g/dL)

mean ± SD

13.4

1.4

Uric acid (mg/dL)

mean ± SD

4.8

1.3

Albumin (mg/dL)

mean ± SD

4.4

0.3

g-GTP (mg/dL)

mean ± SD

33.9

58.6

Creatine (mg/dL)

mean ± SD

0.74

0.32

Cholesterol (mg/dL)

mean ± SD

186.6

38.2

Osteosarcopenia according to general characteristics

The normal group comprised 34% (301/885), the only osteopenia group 33.7% (298/885), the only sarcopenia group 13.1% (116/885), and the OS group 19.2% (116/885). (Table 2)

Table 2

Osteosarcopenia according to general characteristics

Variables

Normal

Only Osteopenia

Only Sarcopenia

Osteo-sarcopenia

p- value

   

N

(%)

N

(%)

N

(%)

N

(%)

 

Total

 

301

34.0

298

33.7

116

13.1

170

19.2

 

Sex

Male

172

59.1

75

25.8

26

8.9

18

6.2

< .001

Female

129

21.7

223

37.5

90

15.2

152

25.6

 

Age (years)

mean ± SD

68.2

5.1

68.8

5.9

73.1

5.5

75.0

5.8

< .001

Spouse

Yes

241

43.0

193

34.4

54

9.6

73

13.0

< .001

No

60

18.5

105

32.4

62

19.1

97

29.9

 

Economic status

Low

76

28.4

87

32.5

45

16.8

60

22.4

0.002

Middle

153

32.9

168

36.1

56

12.0

88

18.9

 

High

72

47.4

43

28.3

15

9.9

22

14.5

 

Smoking

No

273

33.3

274

33.5

112

13.7

160

19.5

0.175

Yes

28

42.4

24

36.4

4

6.1

10

15.2

 

Hypertension

No

141

32.2

178

40.6

46

10.5

73

16.7

< .001

Yes

160

35.8

120

26.8

70

15.7

97

21.7

 

Diabetes mellitus

No

227

32.8

252

36.4

79

11.4

135

19.5

0.001

Yes

74

38.5

46

24.0

37

19.3

35

18.2

 

Hb (g/dL)

mean ± SD

13.9

1.4

13.4

1.4

13.0

1.3

12.7

1.2

< .001

Uric acid (mg/dL)

mean ± SD

5.1

1.4

4.5

1.2

4.7

1.3

4.5

1.2

< .001

Albumin (mg/dL)

mean ± SD

4.5

0.3

4.4

0.3

4.4

0.3

4.3

0.3

< .001

γ-GTP (mg/dL)

mean ± SD

38.7

56.4

30.9

45.8

40.3

102.2

26.1

37.1

0.065

Creatine (mg/dL)

mean ± SD

0.8

0.4

0.7

0.3

0.7

0.2

0.7

0.2

< .001

Cholesterol (mg/dL)

mean ± SD

181.8

38.9

190.6

35.6

177.8

34.0

194.3

41.6

< .001

The distribution of osteosarcopenia by male and female was significantly different (p < 0.001), and age was statistically higher in the OS group (75 ± 5.8 years, P < 0.001) compared to other groups. There was also a statistical difference by spouse's presence (p < 0.001) and at the economic level, the low group had a significant difference of osetosarcoipenia (22.4%), while the group with a high economic level (14.5%) (p = 0.002). The distribution of osteosarcopenia was also significantly different depending on whether hypertension and diabetes were present (p < 0.001).

In addition, hemoglobin, uric acid, albumin, creatine and cholesterol levels were also significantly different among the OS group (p < 0.001).

WHODAS, Kaigo-Yobo, GDSSF scores according to the presence of osteosarcopenia after adjusting covariates

WHODAS disability scores were normal (8.62 ± 1.20), only osteopenia (9.44 ± 1.20), only sarcopenia (16.36 ± 1.48), and OS (17.46 ± 1.35); the OS group had statistically significantly higher WHODAS scores compared to the other groups (P < 0.001). (Fig. 1A)

The Kaigo-Yobo frailty scores were normal (1.60 ± 0.18), only osteopenia (1.88 ± 0.18), only sarcopenia (2.74 ± 0.23), and OS (2.95 ± 0.21); the OS group had statistically significantly higher Kaigo-Yobo scores compared to the other groups (P < 0.001). (Fig. 1B)

The GDSSF depression scores were normal (2.72 ± 0.34), only osteopenia (3.05 ± 0.34), only sarcopenia (4.31 ± 0.42), and OS (4.63 ± 0.38); the OS group had statistically significantly higher GDSSF scores than the other groups (P < 0.001). (Table 3) (Fig. 1C)

Table 3

WHODAS, Kaigo-Yobo, GDSSF score according to the presence of osteosarcopenia

 

Normal

Only Osteopenia

Only Sarcopenia

Osteosarcopenia

p value

mean

SE

95% CI

mean

SE

95% CI

mean

SE

95% CI

mean

SE

95% CI

*WHODAS

8.62

1.20

6.26–10.97

9.44

1.20

7.10–11.79

16.36

1.48

13.46–19.26

17.46

1.35

14.82–20.10

< 0.001

*Kaigo-Yobo

1.60

0.18

1.24–1.96

1.88

0.18

1.52–2.24

2.74

0.23

2.30–3.19

2.95

0.21

2.55–3.35

< 0.001

*GDSSF

2.72

0.34

2.05–3.39

3.05

0.34

2.38–3.71

4.31

0.42

3.48–5.13

4.63

0.38

3.87–5.38

< 0.001

* Adjusting factors: Age, Sex, Spouse, Economic status, Smoking, Hypertension, Diabetes mellitus, Osteopenia, Sarcopenia, Hb, Uric acid, Albumin, γ-GTP, Creatine, Cholesterol
WHODAS: World Health Organization Disability Assessment Schedule. GDSSF: Geriatric Depression Scale-Short Form

Discussion

The main findings of this study were: (1) the prevalence of OS in the community using the new AWGS 2019 criteria was 19.2%; (2) the prevalence of OS was significantly higher in older women; (3) Hb and albumin levels were lower in subjects with OS; and (4) WHODAS, Kaigo-Yobo, and GDSSF scores were all higher in the OS group after adjusting for general characteristics that were different among the four groups. Therefore, we suggest that osteosarcopenia exacerbates frailty, disability and depression, thereby increasing susceptibility to various chronic diseases.

Huo et al. [21] conducted a cross-sectional study of 680 community-dwelling older individuals and reported that the percentage with OS was almost 40%. A study of community-dwelling Chinese elders (older than age 65) found the prevalence of OS to be 10.4% in men and 15.1% in women. In this study, we observed a prevalence similar to that of community-dwelling Chinese elders. Although the prevalence of OS varies greatly depending on the criteria for diagnosis of osteopenia or sarcopenia, OS is not uncommon in elderly women in the community. In particular, considering the commonality of concomitant osteopenia (including osteoporosis) and sarcopenia in the community, DEXA analyses should measure not only bone density but also muscle mass.

Our results suggest that, in elderly women suspected of being malnourished (low Hb, albumin levels), there may be a risk of impairment due to reduced muscle mass and strength and decreased bone density. There is also a high risk of disability and frailty in these subjects.

WHODAS disability scores were significantly higher in the only osteopenia, only sarcopenia, and OS groups compared to the normal group. Frailty and depression scores were significantly higher in the only sarcopenia and OS groups than in the normal and osteopenia alone groups. Therefore, BMD test performance should be accompanied by the sarcopenia test.

For OS, fall, fracture and mortality rates have been reported to be higher than those with bone loss only or muscle loss only, but other studies have reported different results. [22, 23] However, there are no studies reporting on associations with disability and frailty among these groups. Compared to the osteopenia alone group, the WHODAS score showed a clinically significant difference of 8.8 points when sarcopenia was present suggesting that depression is more likely to impact people with sarcopenia than osteopenia. This is consistent with the results of previous research that identified a correlation between disability, frailty, and depression and sarcopenia. While osteopenia was assessed only by bone density testing, sarcopenia was diagnosed as having a decrease in muscle mass as well as a decrease in muscle strength (function), which may be lower in disability, frailty, and depression. In other words, osteopenia may not have progressed to the point of requiring treatment for assistance in daily life activities. However, sarcopenia may be associated with more activity limitation than osteopenia (not osteoporosis)

This study has several limitations. First, the design was cross-sectional. Therefore, causative relationships could not be ascertained. Second, Because the study subjects are not representative samples, caution should be used when expanding the results of the study.

Nevertheless, our research has strength. The study is meaningful as the first to analyze the relationship between OS and disability, depression, and frailty. Future research should not only focus on OS diagnosis and clinical outcomes such as falls, fractures, and death, but also on the OS patient's quality of life and the occurrence of disability.

In conclusion, OS is a relatively common disease in the community and may cause deterioration of health outcomes. Therefore, concurrent evaluation and management of osteopenia and sarcopenia in the elderly is required.

Abbreviations

WHODAS

WHO Disability Assessment Schedule

GDSSF-K

Geriatric Depression Scale-Short Form-Korean

ICD-10-CM

International Classification of Disease, Tenth Revision, Clinical Modification

COPD

chronic obstructive pulmonary disease

OS

osteosarcopenia

MMSE-DS

Mini-Mental State Examination for Dementia Screening

ICF

International Classification of Functionin

AWGS

Asian Working Group for Sarcopenia

DEXA

Dual energy X-ray absorptiometry

ASM

appendicular skeletal muscle mass

SMI

skeletal muscle mass index

Declarations

Ethics approval and consent to participate

All investigations were conducted after obtaining consent which obtained from study participants was written and after being reviewed by the Institutional Review Board of Gyeongsang national university hospital (approval number: GIRB-A16-0012).

 

Consent for publication

Participants provided consent for use of data in research projects. The data are centrally housed at GNUH. The data were accessed after an analysis plan for this manuscript was approved by the GIRB Publications Committee.

 

Availability of data and material

None.

 

Competing interests

All authors have no conflict of interest.

 

Funding

The authors have no support or funding to report.

 

Authors' contributions

All authors read and approved the manuscript.

Conceived and designed the experiments: KS Park and JI Yoo

Analyzed the data: GY Lee, YM Seo, Contributed reagents/materials/analysis tools: SH Seo

Wrote the paper: KS Park and JI Yoo

 

Acknowledgements

This work was supported by the centers for farmer’s safety and health, ministry of agriculture, food, and rural affairs.

 

Conflict of interest

All authors have no conflict of interest.

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