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Peer-Review Record

Examine the Association between Metabolic Syndrome and Frailty in an Older Asian Population

Diabetology 2022, 3(1), 108-116; https://doi.org/10.3390/diabetology3010009
by Hiep Huu Hoang Dao 1, Anh Trung Nguyen 2,3, Huyen Thi Thanh Vu 2,3 and Tu Ngoc Nguyen 1,*
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Diabetology 2022, 3(1), 108-116; https://doi.org/10.3390/diabetology3010009
Submission received: 1 December 2021 / Revised: 2 February 2022 / Accepted: 4 February 2022 / Published: 8 February 2022

Round 1

Reviewer 1 Report

COMMENTS

I would like to congratulate the authors for such an important work. This study provides the preliminary data regarding the association between metabolic syndrome and frailty, which are both highly prevalent in elderly people. The manuscript is also very well-written, clear, and concise. Nevertheless, I have some comments/questions regarding the study which I hope the authors will find helpful to further improve the manuscript.

My main concern with this study is its generalizability. Specifically, the study population included only patients hospitalized in one hospital in Hanoi, the capital city in Vietnam. Furthermore, a third of patients from the primary study (327 of 996 patients) was excluded due to the lack or data regarding metabolic syndrome and frailty. And maybe that’s why the prevalence of frailty and metabolic syndrome in this population is higher than what reported in other study with more general population (Berlin Aging Study II, HOPE study, or the Longitudinal Ageing Study Amsterdam).

My specific comments to the authors are as follows:

  1. In the introduction section, it is not clear why it is important to identify the association between MetS and frailty in the first place. Although the authors have alluded to this in the discussion, adding a sentence or two in the introduction will help the readers to understand better the importance of the study. Furthermore, please use past tense to describe the aim of this study as it has already been done.
  2. In table 4, the authors presented the results from 4 models which had not been clearly specified in the methods, and most importantly, the authors did not specify which model would be used as the ‘main’ model. Furthermore, the authors described that candidate variables for multi-variable logistic regressions were those with p<0.05 in univariate analysis but female gender (p=0.449) and peripheral vascular disease (p=0.830) were included in the multi-variable model 4. Please clarify this.
  3. As I mentioned above, the prevalence of frailty and metabolic syndrome in this population is higher than what reported in other studies, please discuss this.
  4. It also appears that the OR in this study is rather comparable to studies from Europe but not from Asian countries. Can the authors discuss further about why it would be the case and how that affect the interpretation of the results of this study?
  5. It would be great if the authors can compare the baseline characteristics of those with and without missing data about metabolic syndrome and frailty. If the baseline characteristics of the two groups are similar, the results of the current study may be extended to the whole population of the primary study. This should be presented as a supplemental table similar to Table 1.  

Author Response

We would like to thank you for your time spent reviewing our manuscript and for the useful comments. We have specifically responded to the issues raised as detailed below and would be happy to address any further issues if required.

Reviewer 1

I would like to congratulate the authors for such an important work. This study provides the preliminary data regarding the association between metabolic syndrome and frailty, which are both highly prevalent in elderly people. The manuscript is also very well-written, clear, and concise. Nevertheless, I have some comments/questions regarding the study which I hope the authors will find helpful to further improve the manuscript.

My main concern with this study is its generalizability. Specifically, the study population included only patients hospitalized in one hospital in Hanoi, the capital city in Vietnam. Furthermore, a third of patients from the primary study (327 of 996 patients) was excluded due to the lack or data regarding metabolic syndrome and frailty. And maybe that’s why the prevalence of frailty and metabolic syndrome in this population is higher than what reported in other study with more general population (Berlin Aging Study II, HOPE study, or the Longitudinal Ageing Study Amsterdam).

My specific comments to the authors are as follows:

  1. In the introduction section, it is not clear why it is important to identify the association between MetS and frailty in the first place. Although the authors have alluded to this in the discussion, adding a sentence or two in the introduction will help the readers to understand better the importance of the study. Furthermore, please use past tense to describe the aim of this study as it has already been done.

 

Response: We have added further justification in the Introduction (lines 51-53). We also changed “aims” to “aimed” (line 57).

 

  1. In table 4, the authors presented the results from 4 models which had not been clearly specified in the methods, and most importantly, the authors did not specify which model would be used as the ‘main’ model.

Furthermore, the authors described that candidate variables for multi-variable logistic regressions were those with p<0.05 in univariate analysis but female gender (p=0.449) and peripheral vascular disease (PVD) (p=0.830) were included in the multi-variable model 4. Please clarify this.

 

Response: We made a mistake with PVD. We have run the model again without PVD and updated the odd ratios for Model 5 (please see Table 4). Model 5 is the main model.

 

  1. As I mentioned above, the prevalence of frailty and metabolic syndrome in this population is higher than what reported in other studies, please discuss this.

 

Response: We have added this sentence in the Discussion (lines 257-258):

“This may explain why the prevalence of frailty and MetS in our studied population was higher than what reported in other studies with more general populations”

 

  1. It also appears that the OR in this study is rather comparable to studies from Europe but not from Asian countries. Can the authors discuss further about why it would be the case and how that affect the interpretation of the results of this study?

 

Response: This may be due to differences in frailty definition.

In Chao’s study, they also used Fried’s frailty criteria, but frailty and prefrailty were combined: the presence of MetS were associated with a significantly higher risk of combined frailty/prefrailty (OR 2.53, 95%CI 1.78-3.60).

In Lee’s study, frailty was defined by the Frailty Index: metabolic syndrome was strongly associated with frailty status defined by a Frailty Index ≥0.25 (OR 3.2, 95%CI 1.7-6.0)

 

  1. It would be great if the authors can compare the baseline characteristics of those with and without missing data about metabolic syndrome and frailty. If the baseline characteristics of the two groups are similar, the results of the current study may be extended to the whole population of the primary study. This should be presented as a supplemental table similar to Table 1.  

 

Response: We have provided the additional information in the Supplementary Table below. Compared to those included in this study, participants who were excluded were older and had higher prevalence of heart failure, chronic obstructive pulmonary disease, hypertension, and hospitalization in the past year. That may partly explain why they could not complete the measurements for frailty and metabolic syndrome.

Supplementary Table 1. Comparison between participants included and excluded from this study

 

All 

(N=996)

Included

(N=669)

Excluded (due to missing data of frailty and metabolic syndrome)

(N=327)

P-values

Age (years)

71.74 ± 8.61

71.11 ± 8.55

73.03 ± 8.61

<0.001

Female 

598 (60.0%)

403 (60.2%)

195 (59.6%)

0.854

Body mass index (kg/m2)

21.80 ± 3.28

21.77 ± 3.43

21.86 ± 2.97

0.668

Low education

239 (24.1%)

166 (24.8%)

73 (22.5%)

0.430

Malnutrition (MNA <7)

68 (7.3%)

57 (8.7%)

11 (4.0%)

0.012

Having history of hospitalization in the past year

472 (48.2%)

304 (45.9%)

168 (52.8%)

0.043

Comorbidities:

Charlson Comorbidity Index

1.52 ± 1.24

1.51 ± 1.21

1.54 ± 1.30

0.781

Hypertension

521 (52.3%)

318 (47.5%)

203 (62.1%)

<0.001

Diabetes

195 (19.6%)

133 (19.9%)

62 (19.0%)

0.731

Myocardial infarction

26 (2.6%)

18 (2.7%)

8 (2.4%)

0.821

Heart failure

24 (2.4%)

10 (1.5%)

14 (4.3%)

0.007

Stroke

36 (3.6%)

25 (3.7%)

11 (3.4%)

0.767

Peripheral vascular disease

49 (4.9%)

30 (4.5%)

19 (5.8%)

0.364

Chronic kidney disease

480 (54.4%)

354 (53.5%)

126 (57.0%)

0.360

Chronic obstructive pulmonary disease

318 (31.9%)

251 (37.5%)

67 (20.5%)

<0.001

Cancer 

15 (1.5%)

10 (1.5%)

5 (1.5%)

0.967

Dementia

6 (0.6%)

4 (0.6%)

2 (0.6%)

0.979

Continuous data are presented as mean ± standard deviation. Categorical data are shown as n (%). MNA, Mini Nutritional Assessment.

Reviewer 2 Report

Comments to the Author

This is a practically important research indicates that Examine the association between metabolic syndrome and frailty in an older Asian population.

 

However, it is necessary to reexamine the research method etc. in several respects.

1. Result, Table 1. Participant characteristics.

Please add the following clinical data values.

Quantitative variable: fasting serum blood glucose level (mg/dl), serum triglyceride level (mg/dl), HDL cholesterol level (mg/dl), systolic blood pressure level (mmHg), diastolic blood pressure level (mmHg), waist circumference (cm), MET-minutes per week (met/week), grip strength (kg), gait speed (m/sec), body weight loss (kg/ one year).

Categorical variable: Abdominal obesity (waist circumference ≥102 cm in men, and ≥88 cm in women), fasting blood glucose ≥100 mg/dl or having a history of diabetes, SBP ≥130 mmHg or DBP ≥85 mmHg or having a history of hypertension, HDL cholesterol <40 mg/dl in men or < 50 mg/dl in women, Triglyceride ≥150 mg/dl.

2. Discussion

Overall, the prevalence of frailty was higher in participants with MetS than in participants without MetS (Figure 1). MetS was more prevalent in women (71.2% vs. 48.9% in men, p<0.001, Table 2). However, logistic regression, there was not a significant relationship between the women and an increased risk of frailty (Table 3).

Please discuss the differences in the relationship between MetS and frailty in women. (For example, the difference between frailty men and women.)

Author Response

We would like to thank you for your time spent reviewing our manuscript and for the useful comments. We have specifically responded to the issues raised as detailed below and would be happy to address any further issues if required.

Reviewer 2

This is a practically important research indicates that Examine the association between metabolic syndrome and frailty in an older Asian population. 

However, it is necessary to reexamine the research method etc. in several respects.

  1. Result, Table 1. Participant characteristics.

Please add the following clinical data values.

Quantitative variable: fasting serum blood glucose level (mg/dl), serum triglyceride level (mg/dl), HDL cholesterol level (mg/dl), systolic blood pressure level (mmHg), diastolic blood pressure level (mmHg), waist circumference (cm), MET-minutes per week (met/week), grip strength (kg), gait speed (m/sec), body weight loss (kg/ one year).

Response: We have added the additional information in the Table 1 (Please see Table 1, pages 4-5). Details of the exact amount of body weight loss (kg per year) were not recorded in the dataset. Most participants did not remember exactly the amount of body weight loss. In those cases, we asked the participants if they had an estimated weight loss of ≥ 4.5 kg in the last year.

Categorical variable: Abdominal obesity (waist circumference ≥102 cm in men, and ≥88 cm in women), fasting blood glucose ≥100 mg/dl or having a history of diabetes, SBP ≥130 mmHg or DBP ≥85 mmHg or having a history of hypertension, HDL cholesterol <40 mg/dl in men or < 50 mg/dl in women, Triglyceride ≥150 mg/dl.

Response: We have addressed this in the modified Table 2. We have changed Table 2 into “The prevalence of metabolic syndrome and its components by frailty status” and removed the data by gender to avoid confusion.

 

  1. Discussion

Overall, the prevalence of frailty was higher in participants with MetS than in participants without MetS (Figure 1). MetS was more prevalent in women (71.2% vs. 48.9% in men, p<0.001, Table 2). However, logistic regression, there was not a significant relationship between the women and an increased risk of frailty (Table 3). Please discuss the differences in the relationship between MetS and frailty in women. (For example, the difference between frailty men and women.)

Response: The non-significant relationship between the women and an increased risk of frailty on univariate analysis may be due to inadequate sample size. This study was not designed to answer the question of sex differences in frailty or in metabolic syndrome, but of the difference in frailty between people with and without metabolic syndrome. As mentioned above, we have removed the data by gender and modified Table 2 to avoid confusion.

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