An association analysis between hypertension, dementia, and depression and the phases of pre-sarcopenia to sarcopenia: A cross-sectional analysis

Takeshi Endo; Kenju Akai; Tsunetaka Kijima; Shigetaka Kitahara; Takafumi Abe; Miwako Takeda; Toru Nabika; Shozo Yano; Minoru Isomura

doi:10.1371/journal.pone.0252784

. 2021 Jul 22;16(7):e0252784. doi: 10.1371/journal.pone.0252784

An association analysis between hypertension, dementia, and depression and the phases of pre-sarcopenia to sarcopenia: A cross-sectional analysis

Takeshi Endo ^1,^2,^*,^#, Kenju Akai ^2,^#, Tsunetaka Kijima ^2,^3,^#, Shigetaka Kitahara ^4,^‡, Takafumi Abe ^2,^‡, Miwako Takeda ^2,^‡, Toru Nabika ^2,^5,^‡, Shozo Yano ^2,^6,^‡, Minoru Isomura ^2,^7,^‡

Editor: Masaki Mogi⁸

PMCID: PMC8297796 PMID: 34292967

Abstract

Sarcopenia is intricately related to aging associated diseases, such as neuropsychiatric disorders, oral status, and chronic diseases. Dementia and depression are interconnected and also related to sarcopenia. The preliminary shift from robust to sarcopenia (i.e., pre-sarcopenia) is an important albeit underdiscussed stage and is the focus of this study. Identifying factors associated with pre-sarcopenia may lead to sarcopenia prevention. To separately examine the effects of dementia and depression on pre-sarcopenia/sarcopenia, we conducted multiple analyses. This cross-sectional study used health checkup data from a rural Japanese island. The participants were aged 60 years and above, and the data included muscle mass, gait speed, handgrip strength, oral status (teeth and denture), chronic diseases (e.g., hypertension), dementia (cognitive assessment for dementia, iPad Version), and depression (self-rating depression scale). A total of 753 older adult participants were divided into the sarcopenia (n = 30), pre-sarcopenia (n = 125), and robust (n = 598) groups. An ordered logit regression analysis indicated that age and depression were positively correlated with sarcopenia, while hypertension was negatively associated with it. A multiple logistic regression analysis between the robust and pre-sarcopenia groups showed significant associations between the same three variables. Depression was associated with pre-sarcopenia, but not dementia. There was also a significant association between hypertension and pre-sarcopenia. Further research is needed to reveal whether the management of these factors can prevent sarcopenia.

Introduction

Sarcopenia is a geriatric syndrome, characterized by age-related weakness of skeletal muscles as well as loss of muscle strength and physical function [1]. Jang et al. demonstrated the possibility that spectrums of sarcopenia may be in a continuous state of change that correlates with measures of frailty [2,3]. Exercise and nutritional therapies have been developed to prevent sarcopenia, although they are still under-discussed [4–6]. With aging, neuropsychiatric disorders (dementia and depression), oral status, history of fall, and chronic diseases are intricately linked to sarcopenia [7–14]. When analyzing the association between sarcopenia and dementia, depression may act as a confounding factor because cognitive decline due to depression may result in the person being misdiagnosed as having dementia, or in some cases, the two may be merged [15–18]. Previous research has analyzed the relationships between sarcopenia, oral frailty, chronic diseases, and dementia, but the relationship between sarcopenia and depression has so far been unexplored [19].

Older people can be classified into three stages: robust, pre-sarcopenia (i.e., decrease in muscle mass, but not in gait speed or grip strength), and sarcopenia. Pre-sarcopenia is the stage of shift from robust to sarcopenia [20]. Previous studies have shown that people who are not considered to have sarcopenia because of preserved grip strength also have an increased risk for adverse outcomes [2]. A prospective study on the association between osteoporosis and pre-sarcopenia indicated that identifying additional pre-sarcopenia–related factors could help prevent sarcopenia [21]. These issues prompted us to employ a multi-dimensional approach for the study of sarcopenia [22].

Prevention of sarcopenia is important to continue living in rural islands because of the limited number of care facilities and inpatient beds. We previously conducted observational studies in the rural areas of Shimane prefecture in Japan to analyze factors such as depression, dementia, pain, and hypertension that make it difficult for people to live there [23–27]. The issue remained to analyze the relationship between these factors and sarcopenia in rural islands. Oki-islands, which is a group of rural islands in the Shimane prefecture, consist of four islands, Dogo, Ama-town, and so on (S1 Fig). The residents of these islands were aging and displayed high rates of dementia [28]. A significant association between depression and physical activity was found in data from Dogo [29]. Another survey revealed that in Dogo, the rate of residents with hypertension is higher than the overall average of the Shimane prefecture, while the rate of medication treatment for hypertension is lower [30]. Hypertension has been reported to reduce the risk of sarcopenia [31] and is considered an important variable that needs further analysis.

The purpose of this study is to examine the variables that influence the progressing stages of sarcopenia that impact robust, pre-sarcopenia, and sarcopenia in the residents of Oki-island. We hypothesized that depression and dementia have a positive effect, while hypertension has a negative effect, on the progression stages of sarcopenia.

Materials and methods

Participants

We used survey data from Dogo, one of the Oki Islands in Shimane prefecture, Japan. The island has a very high aging rate at 38.4% (as reported in 2015). As of October 1, 2015, the population of Dogo was 14,608, of which 5,609 individuals were aged 60 years and above. Sampling took place in multiple health centers in Dogo, and the study population consisted of the participants of an annual health checkup conducted in June 2016. A total of 805 community-dwelling Japanese people over 60 years of age participated in this study, accounting for 14.4% of the island’s older population. The inclusion criteria for this study were as follows: (1) individuals who had been tested for sarcopenia, (2) individuals assessed for depression and dementia, and (3) individuals who consented to participate after being informed of the protocol and purpose of the current study. Excluding missing data, 753 participants were included in the analysis (Fig 1).

Design and ethical considerations

All residents of the town of Oki Islands over the age of 40 have the right to undergo a health examination once a year with public medical insurance. This health examination covers almost all residents of this age group on the island. There are two types of health examination: group health examination at health centers and individual health examination at medical institutions. The Center for Community-Based Healthcare Research and Education (CoHRE) of Shimane University undertakes the group health examination on the island. Because the group health examination is conducted based on the individual’s own initiative, there is neither verbal consent nor written consent. In addition, Japanese law does not require confirmation of dementia status. Since 2006, CoHRE has been inviting residents to participate in a cohort study (Shimane CoHRE study) to identify factors that may be causing difficulties in their lives in addition to the group health examination. This is the first analysis conducted using a cross-sectional study. The authors of this paper, who belonged to CoHRE, planned, acquired data, and created the database.

Participants in this study were all participants in the group health examination. The following procedures were used to obtain written consent for the cohort study for health screening participants: 1) To ensure that the participant (including the proxy) has time to consider participation in the study, paper information about the study was provided to the participant (including the proxy) at least once before the study was conducted. 2) On the day of the study, a new, easy-to-understand explanation was given orally according to the patient’s level of understanding. 3) When consent was deemed necessary from the proxy for reasons such as cognitive decline, consent was obtained from the proxy after providing a clear explanation, while being careful not to go against the person’s wishes.

The above procedures were approved by the Ethics Committee of Shimane University (#3149) and Unnan City Hospital (#20180004) as being in accordance with the Declaration of Helsinki and ethical guidelines for medical research in Japan. In this study, we used data from the 2016 Shimane CoHRE study in Oki Island town obtained through the above procedures. In this cohort study, the paper questionnaires on daily health status, cognitive function tests using iPads, and physical function tests of grip strength, body composition, and walking speed were conducted in addition to the health examination items (past medical history and other symptoms that were asked about in the interviews, height, weight, and blood pressure measurements, urinalysis, and blood sampling: liver function, lipids, and blood glucose).

Measurement of anthropometry and skeletal muscle mass

Body height was measured using a stadiometer. Muscle mass and body weight were measured using the bioelectrical impedance analysis method with a multi-frequency segmental body composition analyzer (model MC-780A; Tanita Co., Tokyo, Japan) [32]. Body weight and muscle mass of the trunk, arms, and legs (kg) were measured, and the body-mass index (BMI) was calculated. Appendicular skeletal muscle mass was calculated as the sum of the muscle mass of the arms and legs. The muscle mass was divided by the squared height to calculate skeletal muscle index (SMI; kg/m²).

Definition and classification of sarcopenia

In this study, sarcopenia was diagnosed using the criteria of the Asian Working Group for Sarcopenia (AWGS) 2014 [33]. Handgrip strength of each hand was measured twice by using a grip strength dynamometer (Takei Scientific Instruments: Niigata, Japan). Data were collected based on maximum grip strength in kilograms (kg) to the first decimal place. Usual gait speed was measured twice by trained examiners using digital stopwatches on a 5-meter course set between 3- and 8-meter marks on an 11 meter straight, flat, indoor walkway. We asked participants to walk as usual on the walkway course. Results were recorded in seconds to the first decimal place.

The other cutoff points were a grip strength of < 26 kg for men and < 18 kg for women, a usual gait speed of < 0.8 m/s, and an SMI of < 7.0 kg/m² for men and < 5.7 kg/m² for women. Sarcopenia was defined as having a low SMI in addition to low handgrip strength or low usual gait speed. Pre-sarcopenia was defined as having a low SMI with neither low usual gait speed nor low handgrip strength [34]. Robust was defined as not having a low SMI.

Cognitive functions

Screening for depression

We employed the self-rating depression scale (SDS), which has high sensitivity and is suitable for screening depression [35–37]. Based on the SDS score, the following categories were used for determining the participants’ state of depression: “40 points or less: no depression” “41–47 points: mild to moderate depression,” and “48–55 points: moderate to severe depression” [35].

Screening for dementia

The Cognitive Assessment for Dementia, iPad Version (CADi2), is a dementia screening tool that can be completed using an iPad (iPad; Apple Inc., Cupertino, CA, USA). Dementia is assessed based on the number of correctly answered questions and the total response time. The questions assess 10 individual skills, such as immediate recognition and long-term memory. The CADi2 has high sensitivity and specificity, and it is based on criteria that trained persons use to diagnose dementia using neuropsychological tests (the Mini Mental State Examination or Clinical Dementia Rating Scale) [38]. The measured CADi2 score was considered as cognitive decline if the cutoff score was 6 points or less. In addition, participants who were 74 years old or younger and had a response time of 200 seconds or longer or were 75 years old or older and had a response time of 250 seconds or longer, were considered to have cognitive decline regardless of their CADi2 score. In this study, participants who were considered to have such cognitive decline were defined as the dementia group.

Covariates

The reported risk factors for sarcopenia are age, a history of falls, and chronic diseases [1,10,39–41]. The data for the other variables were obtained through self-report questionnaires. We inquired about age, sex (male = 0, female = 1), the number of falls within one year, and chronic diseases (hypertension, dyslipidemia, diabetes, cardio-cerebrovascular disease; no = 0, yes = 1). The presence of chronic diseases was self-reported and included if the participant had been diagnosed by a physician or received medicine.

The use of dentures and the number of remaining teeth were confirmed by a dental hygienist. These parameters are thought to be related to a decrease in masseter muscle thickness, grip strength, and gait speed [42–44].

Statistical analysis

According to the Shapiro-Wilk normality test, all the continuous variables were not normally distributed. The characteristics of study participants in the robust, pre-sarcopenia, and sarcopenia groups were compared using Kruskal-Wallis test for continuous variables and χ² tests for categorical variables. Mann-Whitney U test was used for the dementia and SDS scores. We calculated Spearman’s correlation coefficients for continuous variables. Since the robust, pre-sarcopenia, and sarcopenia groups reflected the order of weakness, ordered logit regression analyses were conducted to determine whether there was an association between each independent variable and pre-sarcopenia and sarcopenia. History of falls was not included in the multivariate analysis because the number of falls was very low and some data were missing. The oral health parameters (remaining teeth, denture), SDS score, dementia, and chronic diseases were selected as covariables with reference to previous studies [14,19].

The following analyses were used to analyze whether these factors were associated with the shift from robust to sarcopenia: multiple logistic regression analysis between robust and pre-sarcopenia/sarcopenia, robust and pre-sarcopenia, pre-sarcopenia and sarcopenia, with the same variables as ordered logit regression analysis. According to these models, coefficients or the adjusted odds ratios (ORs) of the sarcopenia-related parameters were calculated. These multivariate analyses were available for all 753 participants.

The level of significance was set at p < 0.05. All data were presented as medians (interquartile range). All statistical analyses were performed using the STATA 14.2 (StataCorp, College Station, TX).

Results

The characteristics of the 753 participants are shown in Table 1. The median age of the participants was 75.0 years, and the number of participants with pre-sarcopenia (125, 16.6%) was greater than the number with sarcopenia (30, 3.9%). Among the participants in this study, 23.6% had BMI ≥ 25 kg/m² and 2.5% had BMI ≥ 30 kg/m². In the respective order of the robust, pre-sarcopenia, and sarcopenia groups, the participants were significantly older, had a lower BMI, had fewer teeth, and were more likely to have dementia. Hypertension was significantly less common in the pre-sarcopenia group than in the robust group. Although there was no significant difference, the proportion of those using dentures and high SDS scores was higher in the robust than in the pre-sarcopenia and sarcopenia groups.

Table 1. Baseline characteristics of the study participants according to the presence of pre-sarcopenia and sarcopenia (n = 753).

	Robust		Pre-sarcopenia		Sarcopenia		p-value
	n = 598		n = 125		n = 30		p-value
Gender, Female, n (%)	392	65.6	77	61.6	25	83.3	0.08
Age, median (iqr)	74.0	68.0, 80.0	78.0	72.0, 83.0	80.0	77.0, 86.0	< 0.01
Body height cm, median (iqr)	153.6	148.3, 161.4	154.6	149.1, 162.3	148.1	142.5, 155.1	< 0.01
Body weight kg,median (iqr)	56.5	50.7, 64.0	48.0	44.3, 51.9	42.6	38.6, 47.9	< 0.01
BMI kg/m2, median (iqr)	23.6	21.8, 25.5	19.9	18.9, 21.1	20.1	18.4, 21.9	< 0.01
Remaining teeth, median (iqr)	18.0	6.0, 25.0	13.0	2.0, 25.0	12.0	2.0, 21.0	0.06
Denture, n (%)	331	55.4	79	63.2	21	70.0	0.10
Hypertension, n (%)	270	45.2	45	36.0	19	63.3	0.02
Dyslipidemia, n (%)	163	27.3	27	21.6	11	36.7	0.18
Diabetes mellitus, n (%)	59	9.9	14	11.2	7	23.3	0.06
Cardio-CVD, n (%)	81	13.5	14	11.2	4	13.3	0.54
Dementia, n (%)	30	5.0	12	9.6	7	23.3	< 0.01
Fall within 1 year, mean (SD) a)	0.3	1.3	0.2	0.6	0.4	0.7	0.37
SDS, median (iqr)	34.0	29.0, 39.0	35.0	31.0, 41.0	37.5	29.0, 46.0	0.06
SDS score over 40, n (%)	145	24.2	34	27.2	12.0	40.0	0.14
Usual gait speed m/s, median (iqr)	1.3	1.1, 1.4	1.3	1.1, 1.4	1.1	0.7, 1.3	< 0.01
Hand grip strength kg, median (iqr)	25.8	22.0, 34.0	25.4	21.1, 31.3	17.3	15.8, 19.0	< 0.01
SMI kg/m2, median (iqr)	6.8	6.2, 7.6	5.6	5.4, 6.4	5.2	4.9, 5.5	< 0.01

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Note. ・Statistical significance of the differences between groups was determined using Kruskal-Wallis test for continuous variables and χ2 tests for categorical variables.

・Bold shows significance p < 0.05.

・OR: Odds ratios, CI: Confidence intervals.

・Abbreviations: BMI body mass index, CVD cerebrovascular disease, SDS Self-rating depression scale, SMI skeletal muscle index, iqr interquartile range, SD standard deviation.

^aThe number of data points for this variable was 735. Mean values and SD were computed instead of median because of the small sample size in the sarcopenia group.

The number of participants with dementia was 49 (6.5%) and the Mann-Whitney U test did not show a significant association between dementia and SDS scores (S1 Table). The ordered logit regression analysis indicated that age and self-reported depression were positively related to sarcopenia. On the contrary, there was a significantly negative association between hypertension and sarcopenia (Table 2). Two multiple logistic regression analysis between the robust and pre-sarcopenia/sarcopenia combined groups (Table 3) and the robust and pre-sarcopenia groups (Table 4) showed that the three variables were similarly significantly associated: age, self-reported depression, and hypertension were related to sarcopenia. Conversely, in the multiple logistic regression analysis between the pre-sarcopenia and robust groups, the only factor significantly associated was sex (i.e., female) (Table 5). The variance inflation factors of the variables used in the multivariate analysis conducted in this study were less than 10.

Table 2. Multivariate ordered logit regression analysis for robust, pre-sarcopenia, and sarcopenia (n = 753).

	Coef	95% CI	p-value
Age	0.09	0.06–0.12	< 0.01
Sex (Female)	0.03	-0.38–0.43	0.90
Remaining teeth	0.00	-0.02–0.03	0.84
Denture	-0.001	-0.53–0.53	0.998
Hypertension	-0.47	-0.87–0.60	0.02
Dyslipidemia	-0.23	-0.67–0.21	0.31
Diabetes mellitus	0.47	-1.00–1.06	0.11
Cardio-cerebrovascular disease	-0.42	-1.00–0.16	0.16
Dementia	0.56	-0.80–1.19	0.09
Self-rating depression scale	0.04	0.01–0.06	0.03

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Note. Objective variables were scored as robust = 0, pre-sarcopenia = 1, sarcopenia = 2. Chronic diseases: no = 0, yes = 1.

Table 3. Multivariate logistic regression analysis between pre-sarcopenia and sarcopenia groups combined and robust.

(n = 753).

	OR	95% CI	p-value
Age	1.09	1.06–1.13	< 0.01
Sex (female)	0.97	0.65–1.46	0.89
Remaining teeth	1.00	0.98–1.03	0.81
Denture	1.02	0.60–1.72	0.95
Hypertension	0.60	0.40–0.90	0.01
Dyslipidemia	0.79	0.51–1.24	0.31
Diabetes mellitus	1.50	0.83–2.70	0.18
Cardio-cerebrovascular disease	0.66	0.37–1.20	0.17
Dementia	1.65	0.86–3.15	0.13
Self-rating depression scale	1.03	1.01–1.06	0.01

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Note. Objective variables were scored as robust = 0, pre-sarcopenia and sarcopenia combined group = 1. Chronic diseases: no = 0, yes = 1.

Table 4. Multivariate logistic regression analysis between robust and pre-sarcopenia (n = 723).

	OR	95% CI	p-value
Age	1.08	1.05–1.12	< 0.01
Sex (female)	0.79	0.51–1.22	0.29
Remaining teeth	1.00	0.97–1.03	0.91
Denture	0.97	0.54–1.73	0.91
Hypertension	0.51	0.33–0.80	< 0.01
Dyslipidemia	0.74	0.45–1.21	0.23
Diabetes mellitus	1.27	0.65–2.47	0.49
Cardio-cerebrovascular disease	0.68	0.36–1.29	0.24
Dementia	1.25	0.59–2.63	0.56
Self-rating depression scale	1.03	1.00–1.06	0.04

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Note. Objective variables were scored as robust = 0, pre-sarcopenia = 1. Chronic diseases: no = 0, yes = 1.

Table 5. Multivariate logistic regression analysis between pre-sarcopenia (0) and sarcopenia (1) (n = 155).

	OR	95% CI	p-value
Age	1.06	0.97–1.15	0.18
Sex (Female)	5.66	1.50–21.4	0.01
Remaining teeth	0.98	0.93–1.05	0.63
Denture	0.96	0.27–3.43	0.95
Hypertension	1.76	0.68–4.59	0.25
Dyslipidemia	1.28	0.48–3.44	0.62
Diabetes mellitus	3.24	0.91–11.5	0.07
Cardio-cerebrovascular disease	1.19	0.30–4.70	0.81
Dementia	2.79	0.82–9.48	0.10
Self-rating depression scale	1.05	0.99–1.11	0.09

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Note. Objective variables were scored as pre-sarcopenia = 0, sarcopenia = 1. Chronic diseases: no = 0, yes = 1.

S2 Table shows the Spearman’s correlation coefficients. The BMI was not included as a variable in the multivariate analysis because of its high correlation with SMI used in the diagnostic criteria for sarcopenia. The variance inflation factors of the variables used in the multivariate analysis conducted in this study were less than 10. S3 Table shows the number of participants who fell below the diagnostic criteria for sarcopenia was divided by sex and sub-category (pre-sarcopenia and sarcopenia).

Discussion

According to the robust, pre-sarcopenia, and sarcopenia groups, results showed that participants were older in age, had a lower BMI, fewer number of teeth, and a higher SDS score, and a higher proportion had dementia. These results indicated that a steady decline in individuals’ mental and physical status, led to the development of sarcopenia; moreover, this finding is consistent with a previous study, indicating that the shift from robust to sarcopenia is a continuous state of change that correlates with frailty [2].

We found multiple factors associated with the progression from robust to pre-sarcopenia and sarcopenia. In the progression of stages from robust to pre-sarcopenia, in addition to age, depression and hypertension were significantly associated with the participants’ status.

The high depressive tendency in our study might be the reason why there was a significant association between self-reported depression and sarcopenia. A report showed that increased depression severity was associated with sarcopenia [45]. The relationship between depression and sarcopenia remains under discussion. In the Korean study that did not find a significant association between sarcopenia and depression, 16.6% of the sarcopenia participants and 14.4% of the non-sarcopenia participants had depressive tendencies [46]. Others have reported the opposite [14,47,48]. Hsu et al. reported that the rate of depressed participants was 29.8% in the sarcopenia group and 14.3% in the non-sarcopenia group and depression was significantly associated with sarcopenia [14]. In our study, the proportion of participants judged as depressed (a score over 40 points on the SDS) was even higher. The relationship between depression and sarcopenia can be justified by the commonly associated factors such as inactivity [49] and chronic inflammation [50,51].

In the present study, there was no significant association between dementia and sarcopenia. The possible reason why sarcopenia and dementia were not significantly related was the small number of dementia and sarcopenia participants. In the present study, there was no significant association between dementia and sarcopenia. The sarcopenia rate in our study was 3.9%, lower than in a previous study which reported a rate of approximately 10.0% [52,53]. This may be because the participants in our study were active enough to participate in a voluntary health checkup, whereas bedridden and institutionalized residents could not participate in the checkups. The dementia rate in our study was 6.5%, which was smaller than that reported by a nearby island’s study showing 16.4% dementia in the general population of Ama-town [28]. Hsu et al. (2014) indicated that both dementia and depression were significantly associated with sarcopenia. In their study, the rate of participants with sarcopenia was 30.9% and of those with dementia was 38.0% [14]. These rates were clearly different from those in our study. Other studies analyzing the relationship between sarcopenia and dementia did not include depression as a variable; hence, they could not be compared with our study [54–56].

Depression did not have a confounding effect on the association between dementia and sarcopenia. Firstly in our study, there was no significant association between the SDS score and dementia, which indicated that depressive tendencies did not significantly influence the CADi test to determine dementia, although a previous study showed that depression affects cognitive function [17]. Secondly, we conducted the ordered logit regression analyses including both dementia and depression.

In this study, hypertension was significantly less common in pre-sarcopenia patients than in robust patients. This was consistent with a previous study [31]. In general, nutritional therapy and exercise therapy are recommended for the management of hypertension [57], and these two therapies have been reported to be effective in preventing sarcopenia [4,5]. However, the relationship between hypertension and prevention of sarcopenia requires further research.

In this study, there were significantly more females in the sarcopenia group than in the pre-sarcopenia group. The two groups are defined by the difference in muscle strength in which pre-sarcopenia has preserved muscle strength while sarcopenia has decreased muscle strength. According to the AWGS 2014 criteria for sarcopenia, this muscle strength is defined as SMI (<5.7 kg/m2 for female and <7.0 kg/m2 for male) and grip strength (<18 kg for female and <26 kg for male), with a lower cutoff point for women. In the sarcopenia group of this study, it was clear that there were more females with grip weakness than male (S3 Table). Further studies are needed to clarify the causal relationship between sex and this muscle weakness.

Limitations

There are several limitations in this study. First, this was a cross-sectional study; as such, a prospective study will be required to investigate the causal relationships between sarcopenia and its related factors. The second limitation is that participation in this cohort study was voluntary, and a random selection of Dogo residents was not used, therefore, selective bias may have occurred. Third, this study was conducted in 2016, and the speed of the 5 m gait was measured according to the AWGS 2014 criteria and not the AWGS 2019 criteria using the 6 m gait. Our future task is to conduct a sarcopenia study using the AWGS 2019 criteria.

Conclusion

Depression was positively associated with the sarcopenia group compared to the robust one, while hypertension was negatively associated. Dementia, however, had no significant effect. The depression scale of the rural island residents needs to be followed up because it can be an associated factor in the future progression of sarcopenia.

Supporting information

S1 Fig. Map showing the location of Dogo, which is one of the Oki Islands.

Published with permission from Oki Islands UNESCO Global Geopark Promotion Committee. Available from: http://www.oki-geopark.jp/en/features/ (accessed July 22, 2020).

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S1 Table. Mann-Whitney U test for the self-rating depression scale according to the presence of dementia (n = 753).

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S2 Table. Spearman’s rank correlations between the participants’ characteristics and sarcopenia-related factors.

* p < 0.10,** p < 0.05, *** p < 0.01.

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S3 Table. The number of participants who fell below the diagnostic criteria for sarcopenia was divided by sex and sub-category (pre-sarcopenia and sarcopenia).

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S1 Dataset

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Click here for additional data file.^{(140.9KB, xlsx)}

Data Availability

There are no ethical or legal restrictions on sharing a de-identified data set, which I uploaded as the additional file.

Funding Statement

The authors received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0252784.r001

Decision Letter 0

Masaki Mogi

14 Dec 2020

PONE-D-20-34154

The transition phase of pre-sarcopenia to sarcopenia association analysis between hypertension, dementia, and depression: A cross-sectional study

PLOS ONE

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

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Reviewer #2: No

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5. Review Comments to the Author

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Reviewer #1: Thank you for your invitation. This is a paper addressing the association between sarcopenia, pre-sarcopenia, and depression in a rural population of older adults. Some important issues need to be considered.

1. Introduction: 1. The authors stated that "sarcopenia is a phenotype of frailty". This statement is not based on evidence. It was just a consideration from some researchers. Some authors argued that frailty and sarcopenia were "two sides of one coin." Please try to use the widely agreement of the definition of sarcopenia, such as EWGSOP2 or AWGS.

2. Introduction: 'Sarcopenia can be classified into three stages: robust, pre-sarcopenia, and sarcopenia'. This statement is not true. Robust is not a stage of sarcopenia. Sarcopenia can be classified into three stages: pre-sarcopenia, sarcopenia, and severe sarcopenia.

3. Figure 1 is not the main results of this paper. It should serve as a supplementary figure, if necessary.

4. This a secondary analysis of a cross-sectional study. This point shouild be clearly stated.

5. We need more details about the handgrip strength measurement and walking speed measurement.

6. The authors defined sarcopenia based on the AWGS 2014. Why didn't they use the AWGS 2019? Would the results significantly change if the AWGS 2019 definition of sarcopenia was applied? Perhaps, the authors can also use the AWGS 2019 criteria and reanalysis their data to perform a sensitivity analysis of their results in order to test the robustness of their conclusion.

7. "Chronic diseases (hypertension, dyslipidemia, diabetes, cardio- 169

cerebrovascular disease; no = 0, yes = 1)" What about other important diseases such as COPD, liver disease, and CKD?

8. Why did the authors not define severe sarcopenia since they have the data on ASMI, handgrip strength, and walking speed?

9. Did the authors consider the multicolinearity in their models?

10. The authors reported that “all the continuous variables were not normally distributed” . However, they reported mean and SD for these variables in Table 1.

11. The prevalence of sarcopenia is extremely low (3.9%) compared to the data in the literature. Is there any explanation for these results? Maybe there are selection bias as the participants were recruited from group health examination. As a result, the generalizability of this paper would be weakened.

Reviewer #2: I found the study titled " The transition phase of pre-sarcopenia to sarcopenia association analysis between hypertension, dementia, and depression: A cross-sectional study" deals an interesting topic on spectrum of sarcopenia in community-dwelling older adults. However, I noted that there are tremendous rooms for improvement for the manuscript to provide enough explanation that the data deserves, and to add some clinical knowledge in the field of geriatrics.

Major points>

1) Throughout the manuscript: By using the term ‘transition’, authors may mislead readers on the nature of the study, since this cross-sectional study only compares clinical factors across non-sarcopenic, pre-sarcopenic, and sarcopenic participants in this community-based study while the term transition usually denotes some longitudinal dynamic changes of a condition.

2) Introduction: This part should be improved to provide rational backgrounds and needs to support the conceptualization of the study hypothesis. Irrelevant remarks in the introduction part (e.g., line 57-58, Cognitive decline due to…) should be removed. In the last part, study hypothesis should be more clearly addressed. Also, on top of previous researches that authors remarked in the last part of the introduction, I hope to see what the current study adds up as a meaningful scientific literature.

3) Analysis/results: While authors used logistic regression analysis, I think factors associated with sarcopenia spectrum can be more clearly assessed using ANCOVA, with no-sarcopenia, presarcopenia, and sarcopenia as independent variables. Maybe as a sensitive analysis. As a recent paper suggested (Jang et al, JCSM 2020 Apr; 11(2): 497–504), spectrums of sarcopenia might be incremental and somehow continuous, highly correlate with frailty spectrum. Therefore, performing multiple comparisons between 3 conditions of no sarcopenia, pre-sarcopenia, and sarcopenia might be less meaningful.

4) Discussion, Line 288: In the current study design, mechanism cannot be drawn. These remarks seem to be rather speculative.

4) Discussion, Line 307: Irrelevant (or less relevant) remarks for current study and analysis.

5) Conclusion: Conclusion should concisely summarize the main hypothesis and corresponding study results, and interpretations from authors.

Minor points>

1) Co-first authors are not marked in the author list

2) I recommend authors rather not to use the term elderly in the scientific literature, (See Vaughan et al, JAGS, 2019 67:211-217), and replace it with case-specific terms such as older people, older participants, individuals etc. While authors are using the term ‘subject’, I also noted that this word can be replaced with ‘participants’ in the present study is an observational study. In choosing words describing sex/gender, I recommend to have some unity, for example sex/male/female vs. gender/men/women

3) Page 8 Line 131, Is the term physique a commonly used word in scientific literature?

4) Table 1, n=753 is everywhere, except for fall item (n=735). I recommend authors to provide total n (753) in general), and provide n of fall item in the note with appropriate quotation marks for the journal. P values should be provided with 3 digits below decimal points. I also opposite in separating table into 2 vertical sections of mean+-sd and n(%), but this might be up to the journal’s policy.

Reviewer #3: This study of a rural Japanese island is very interesting and worthy of publication. The authors suggested that aging, depression, and hypertension were associated with sarcopenia in rural islands. However, there are several major concerns with the manuscript that must be addressed.

Major comments:

1. The authors described traditional risk factors for sarcopenia and the current state of the rural island in the introduction. However, the purpose of the study was unclear, so please include this at the end of the introduction.

2. The presence or absence of obesity (≥25 or 30 kg/m2) is also an important independent factor for sarcopenia; however, why did you mention hypertension, diabetes, and cerebrovascular disease without including obesity?

3. The comparison of the three groups was performed using the Kruskal-Wallis test or χ2 test, but no ad hoc analysis was performed, such as multiple comparison or residual analysis.

4. The prevalence of sarcopenia in this study was 3.9%, which is very low compared with those reported in other studies. It is necessary to explain the reason and characteristics of the low prevalence of sarcopenia, including the study of rural islands.

5. There were sex-based differences in this study. Please clarify why you did not analyze by sex.

Minor comments:

1. It is recommended that the island description and figure 1 provided in the introduction are presented in the participants section of Materials and Methods.

2. The current diagnosis of sarcopenia generally uses AWGS2019; however, it is important to explain why AWGS was used.

3. Please add the definition or cutoff for dementia diagnosis by CADi2 in the “screening for dementia” section.

4. The non-normal distribution data in Table 1 should be presented as median and interquartile range.

5. The following research showed that hypertension was a protective factor for sarcopenia. Hence, I recommend that you refer to it as supporting evidence:

Kurose S et al, Sci Rep 10:19129, 2020.

**********

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PLoS One. 2021 Jul 22;16(7):e0252784. doi: 10.1371/journal.pone.0252784.r002

Author response to Decision Letter 0

24 Apr 2021

Response to Reviewer 1

Thank you for pointing out the most fundamental part of the definition and classification of sarcopenia. Please also note that we have included a description of why we did not follow the AWGS 2019 criteria.

Reply: As you pointed out, the description seemed to confuse sarcopenia with frailty, so we changed it to something widely agreed upon.

Revised: Page 4, line 51-54

Reply: Thank you for pointing out this error. We had to differentiate between older people’s medical condition and not sarcopenia. We did not include severe sarcopenia because the purpose of this study was to analyze the characteristics of pre-sarcopenia. Furthermore, the study was conducted in 2016, and we followed the criteria of AGWS 2014 and not AGWS 2019, which incorporated severe sarcopenia. Please see the response to comments 6 and 8 for a more detailed explanation. We have corrected it as follows.

Revised: Page 4, line 63-65

3. Figure 1 is not the main results of this paper. It should serve as a supplementary figure, if necessary.

Reply: I followed your instructions and changed it to a supplementary file.

4. This a secondary analysis of a cross-sectional study. This point should be clearly stated.

Reply: This is the first analysis conducted by a cross-sectional study. The authors of this paper, who belonged to CoHRE, planned, acquired data, and created the database. This part was not written properly, so I added it to the Method section.

Revised: Page 7-8, line 116-1185. We need more details about the handgrip strength measurement and walking speed measurement.

Reply: Thank you for pointing this out. I added a note about the measurement method and its definition of decline.

Revised: Page 9-10, Line 148-154 <Method>

Reply: We believe that in remote areas with few medical resources, prevention of sarcopenia is an important issue, and this study focused on extracting the characteristics of pre-sarcopenia. Since the purpose of this study was not properly communicated, I have included the purpose in the last sentence of the introduction so that the purpose is clear again.

The sarcopenia study you mentioned, using the AWGS 2019 criteria, is our next research study. CoHRE is still conducting annual surveys in the same way, and a paper on sarcopenia using the AWGS2019 criteria is being prepared using data from Oki Island.

7. "Chronic diseases (hypertension, dyslipidemia, diabetes, cardio-cerebrovascular disease; no = 0, yes = 1)" What about other important diseases such as COPD, liver disease, and CKD?

Reply: We did not obtain the data that you mentioned at the time of our 2016 survey. We are currently acquiring data on liver diseases and will consider acquiring data on COPD and CKD in the future.

8. Why did the authors not define severe sarcopenia since they have the data on ASMI, handgrip strength, and walking speed?

Reply:

This study was conducted in 2016, and the speed of the 5m gait was measured according to the AWGS 2014 criteria, not the 6m gait used in AWGS 2019. Other methods of case selection such as lower leg circumference and SARC-F recommended by AWGS 2019 were not assessed. Therefore, it is difficult to reanalyze the data using the criteria of AWGS 2019 because the inclusion criteria was different. As a trial, we tried to diagnose severe sarcopenia using the AWGS 2019 criteria using SMI, walking speed, and hand grip strength, but the number of participants was as low as nine. The participants were community-dwelling health screening participants, who had a higher percentage of pre-sarcopenia than sarcopenia. As we noted in reply to comment 6, a sarcopenia study using the AWGS 2019 criteria is our future research.

Revised: Page 6, Line 95-96

9. Did the authors consider the multicolinearity in their models?

Reply: First, the correlation coefficients between each variable were calculated, and adjustments were made so that variables that were strongly correlated, such as BMI and SMI, were not entered simultaneously. Further, both the ordered logistic regression and the variance inflation factor of the variables found in the multiple logistic regression analysis were less than 10. This was added to the results.

Revised: Page 16, Line 246-247 <Result>

10. The authors reported that “all the continuous variables were not normally distributed” . However, they reported mean and SD for these variables in Table 1.

Reply: I created a new table 1 with changes to median and inter quartile range.

Reply: As mentioned in Page19, line 278-281, this study was based on health examination data of relatively active older people who were able to come voluntarily to the study site, and the incidence of sarcopenia was low. The main purpose of this study was to pick up relevant factors in participants with pre-sarcopenia, and we believe that the design was able to fulfill that purpose. However, as you pointed out, the findings of this study do not apply to populations with a high prevalence of sarcopenia, such as community-dwelling older people, including those who are bedridden in home care or institutionalized patients. This was not explained well enough, so I added this information in the discussion section.

Revised:　Page 22, Line 311-313 <Discussion>

Response to Reviewer 2

We greatly appreciate your comments. I learned that sarcopenia is some kind of continuous state change and have revised our manuscript accordingly.

Major points>

Reply: As you pointed out, we realized that using "transition" in our research results misleads people into thinking that it is a longitudinal study. We deleted the word “transition” and changed it to "shift”.

Revised: Page 2, line 27, page 4, line 65, page 6, line 86, page 13, line 207 and page 21, line 289

Reply: The parts you have highlighted were not clearly related to the main discussion; hence, I have deleted the text and made revisions accordingly.

Revised: Page 4, Line 57-60

2) Also, on top of previous researches that authors remarked in the last part of the introduction, I hope to see what the current study adds up as a meaningful scientific literature.

Reply: We believe that prevention of sarcopenia in remote areas where medical resources are scarce is important, and our main focus was to extract the characteristics of pre-sarcopenia. Since we did not explain this purpose properly, we stated it in the last sentence of the introduction to clearly convey the purpose.

Revised: Page 6, Line 84-88

Reply: Thank you for suggesting a better analysis. The purpose of this study is to analyze the process of transition to sarcopenia.

We are in complete agreement that spectrum of sarcopenia is some kind of a continuous. Therefore, we also believe that sarcopenia is a gradual and sequential transition, such as robust, pre-sarcopenia, and sarcopenia, and we conducted ordered logistic regression, a logit analysis that can track the sequential transition. As you pointed out, ANCOVA may be more appropriate if these three are considered continuous. ANCOVA with robust, pre-sarcopenia, and sarcopenia assigned as dependent variables (0, 1, and 2) showed a significant association between age and diabetes mellitus (additional file). Thank you for your guidance on other analysis methods. However, we would like to leave this as a future issue because looking at the correlation between sarcopenia and frailty spectrum with this kind of method is far from the main purpose of this study.

In our introduction and discussion sections, I have added the findings that sarcopenia is some kind of continuous state that correlates with frailty index (Jang et al, JCSM 2020 Apr; 11(2): 497–504). I also learned that the frailty index used here has been studied in the Asian region for a long time and is an index that can be applied to Japanese people without problems (Jung et al, PLoS One. 2014 Feb 4;9(2):e87958). I have also added this finding to the text.

This study is consistent with the purpose of our research, which showed that people with pre-sarcopenia, who are not considered to have sarcopenia because their grip strength is preserved, also have a risk for adverse outcomes. Also, the purpose of comparing these three states and the hypothesis is more clearly stated in the last paragraph of the introduction. Thank you for your suggestion.

Revised: Page 4, Line 52-54 and 65-66<Introduction>

Page 5, Line 66-69 <introduction>

Previous studies have shown that people who are not considered to have sarcopenia because of preserved grip strength also have an increased risk for adverse outcomes .

Page 6, Line 84-88 <Introduction>

The purpose of this study is to examine the variables that influence the process of transition to sarcopenia in the residents of Oki-island. We hypothesized that depression and dementia would affect this shift and conducted ordered logit analysis between these factors, in addition to oral status and hypertension, on pre-sarcopenia and sarcopenia.

Page 21, Line 287-290

These results indicate when there is a steady decline in individuals’ mental and physical status, they develop sarcopenia, and this finding is consistent with a previous study, indicating that the shift from robust to sarcopenia is a continuous state of change that correlates with frailty .

4) Discussion, Line 288: In the current study design, mechanism cannot be drawn. These remarks seem to be rather speculative.

Reply: You pointed out the part where you speculate why hypertension was less in pre-sarcopenia patients. We have added a previous study on the relationship between hypertension and pre-sarcopenia and have stated that our results are consistent with them and made some assumptions about the mechanisms involved.

Revised: Page 23, Line 327-332<Discussion>

5) Discussion, Line 307: Irrelevant (or less relevant) remarks for current study and analysis.

Reply: We have confirmed that the content was indeed irrelevant to the text. Therefore, I have deleted the text.

6) Conclusion: Conclusion should concisely summarize the main hypothesis and corresponding study results, and interpretations from authors.

Reply: I clarified the description of the hypothesis in the introduction, and based on that, I revised the conclusion per your suggestion.

Revised: Page 25, Line 351-353 <Conclusion>

Minor points>

1) Co-first authors are not marked in the author list

Reply: The co-first authors are now marked on the title page.

Revised: Page 1, Line 5-6

Reply: We have unified the terminology as you suggested.

Revised: Throughout the entire manuscript.

3) Page 8 Line 131, Is the term physique a commonly used word in scientific literature?

Reply: The term "physique" has been replaced by "anthropometry" because of a misinterpretation of the terminology.

Revised: Page 9, Line 138 <Method>

Reply: We have revised Table 1 accordingly.

Revised: Page 14, Line 227

Response to Reviewer 3

We greatly appreciate your specific guidance on what needs to improve in terms of BMI numbers, incidence of sarcopenia, and AGWS criteria.

Major comments:

Reply: As you pointed out, the part describing the purpose of the research was unclear; hence, I have added it to the last paragraph of the introduction.

Revised: Page 4, Line 52-54 and 65-66<Introduction>

Reply: As you pointed out, BMI is an important index that is also related to muscle mass and mortality [Abramowitz MK, 2018;13(4):e0194697. Epub 2018/04/12], and obesity has been reported to be a risk factor for sarcopenia [Batsis JA, Nat Rev Endocrinol. 2018;14(9):513-37]. BMI was not included as a covariate because skeletal muscle index, one of the diagnostic criteria for sarcopenia, had a very high correlation with BMI. Including BMI in the ordered logistic regression with Robust/Pre-sarcopenia/Sarcopenia as the dependent variable would result in high multicollinearity. However, obesity is a very important index for sarcopenia, and we have added it to the results.

Revised: Page 14, Line 219-220<Result>

Among the participants in this study, 23.6% had BMI ≥ 25 kg/m2 and 2.5% had BMI ≥ 30 kg/m2.

3. The comparison of the three groups was performed using the Kruskal-Wallis test or χ2 test, but no ad hoc analysis was performed, such as multiple comparison or residual analysis.

Reply: The purpose of our study is to show a stepwise trend and not to look at the difference between two groups in an ad hoc multiple comparison. For this reason, we used ordered logistic regression as our method. I explicitly added the reason for using this method in the analysis section.

Reviewer 2 also suggested that we use ANCOVA, and we explained accordingly.

Reply: We thought that the lower prevalence of sarcopenia in this study than in previous studies was due to the fact that the participants were relatively active older people who were able to voluntarily come to the study site. This was also mentioned in Page 22, Line 311-313, but there was no "comparison with sarcopenia prevalence in remote island" as you pointed out. In addition, the fact that the participants did not include bedridden or institutionalized residents may have contributed to this low rate, so we have made the following changes.

Revised: Page 22, Line 311-313

5. There were sex-based differences in this study. Please clarify why you did not analyze by sex.

Reply: As you pointed out, sex was a significantly related variable between the pre-sarcopenia and sarcopenia groups (Table 3.3). However, in the characteristics table (Table 1) and the ordered logistic regression table (Table 2), and multiple logistic regression (Table 3.1, 3.2) sex was not a significantly associated factor. Since the main purpose of this study was to extract the characteristics of pre-sarcopenia and other stages, we did not conduct the analysis with sex as the main axis. The difference between pre-sarcopenia and sarcopenia is not in muscle mass but in muscle strength, that’s why sex may be related to this part. I also made a comparison table of SMI, hand grip strength, and usual gait speed of the two groups and added it to the results as an additional file (S3 table). The reason for the association between women and sarcopenia is that there were more women with sarcopenia who had low hand grip strength. Thank you for presenting a new perspective. I have added the following to the text.

Revised: Page 24, Line 333-341<Discussion>

Minor comments:

1. It is recommended that the island description and figure 1 provided in the introduction are presented in the participants section of Materials and Methods.

Reply: I changed the location of figure 1 as you instructed. Also, as pointed out by another reviewer, I made this figure an additional file because this figure is not what we have clarified in this study.

2. The current diagnosis of sarcopenia generally uses AWGS2019; however, it is important to explain why AWGS was used.

Reply: We believe that in remote areas with few medical resources prevention of sarcopenia is an important issue, and this study focused on extracting the characteristics of pre-sarcopenia. Since the purpose of this study was not properly communicated, I have included it in the last sentence of the introduction so that the purpose is clear again. Also, this study was conducted in 2016, and the speed of the 5m walk was measured according to the AWGS 2014 criteria, not the 6m walk used in AWGS 2019. Other methods of case selection such as lower leg circumference and SARC-F recommended by AWGS 2019 were not assessed. Therefore, it is difficult to reanalyze the data using the criteria of AWGS 2019 because the inclusion criteria was different. As a trial, we tried to diagnose severe sarcopenia using the AWGS 2019 criteria using SMI, walking speed, and hand grip strength, but the number of participants was as low as nine. The participants were community-dwelling health screening participants, who had a higher percentage of pre-sarcopenia than sarcopenia. CoHRE is still conducting annual surveys in the same way, and a paper on sarcopenia using the AWGS 2019 criteria is being prepared using data from Oki Island.

Revised: Page 6, Line 95-96　<Introduction>

3. Please add the definition or cutoff for dementia diagnosis by CADi2 in the “screening for dementia” section.

Reply: As you pointed out, the cut off was unclear. This cognitive function test is somewhat complicated, as the test takes into account not only the score but also the response time. I have added the information to the Method in the text.

Revised: Page 11, Line 175-181, <Method>

4. The non-normal distribution data in Table 1 should be presented as median and interquartile range.

5. The following research showed that hypertension was a protective factor for sarcopenia. Hence, I recommend that you refer to it as supporting evidence:

Kurose S et al, Sci Rep 10:19129, 2020.

Reply: Thank you for the information. We have checked the contents and found them to be very important for our research. I have added it to the introduction and discussion.

Revised: Page 5, Line 82-83 <Introduction>

Revised: Page 23, Line 327-333 <Discussion>

Attachment

Submitted filename: Respons to Reviewers.docx

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PLoS One. doi: 10.1371/journal.pone.0252784.r003

Decision Letter 1

Masaki Mogi

11 May 2021

PONE-D-20-34154R1

An association analysis between hypertension, dementia, and depression and the phases of pre-sarcopenia to sarcopenia: A cross-sectional analysis

PLOS ONE

Dear Dr. Endo,

==============================

The manuscript has been improved; however, several revisions are still necessary in the present form. See the Reviewer #3's comments and respond them appropriately.

==============================

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Masaki Mogi

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #1: I would like to thank the authors for their efforts and time. They have addressed my concerns properly. I have no further questions.

Reviewer #2: I recognized that authors addressed upon reviewers' points appropriately, and improved the work accordingly. I sincerely appreciate for the authors' effort.

Reviewer #3: The revised version has been partially improved. However, there are several major concerns with the manuscript as written that must be addressed.

Major comments:

1. The expression “shifting phase” is inappropriate in this study. Because the authors have not examined the predictors of subject who have shifted from non-sarcopenia to pre-sarcopenia. This study is a cross-sectional study, and its influence on the shifting phase is unclear.

2. SARC-F is not required for sarcopenia diagnosis using AWGS 2019, but can be diagnosed by grip strength, walking speed, and SMI. Therefore, the authors should address a clear reason for using AWGS2014.

3. The comparison of the three groups cannot be mentioned by only the Kruskal-Wallis test (p15, 243-248 line). Multiple comparison analysis is required to confirm these results.

Minor comments:

1. In Table 1, the interquartile range should be indicated by the 1st quartile – 3rd quartile. In addition, the authors should add the items such as pre-sarcopenia, sarcopenia etc in the column.

2. I could not find the S1 and S2 tables in this revised version.

3. The median of age was 74.9 years in this manuscript. However, the mean age of the first manuscript was also 74.9 years. Is it correct?

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

PLoS One. 2021 Jul 22;16(7):e0252784. doi: 10.1371/journal.pone.0252784.r004

Author response to Decision Letter 1

19 May 2021

Response to reviewer 3

Reviewer 3

Major comments:

Reply:

　I changed the word to shifting instead of transition as pointed out by another reviewer.

You are right, the word shifting was inappropriate. I have revised it as follows.

Revised: page, line,

　Page 7, Line 99-103

　Page 21, Line 315-318

Reply:

As you pointed out, the SARC-F is not required for picking up sarcopenia because this study measured all participants. However, in this study, the speed of 5m walking was measured, so the speed of 6m walking is unknown. 6m walking speed should be measured by AWGS 2019 standards. Hence, we could not classify them according to the AWGS2019 criteria. The sentence about SARC-F has been removed from Limitation. I appreciate your pointing out our error.

Revised: page 25, Line 374-377

Third, this study was conducted in 2016, and the speed of the 5 m gait was measured according to the AWGS 2014 criteria and not the AWGS 2019 criteria using the 6 m gait. Our future task is to a conduct a sarcopenia study using the AWGS 2019 criteria.

3. The comparison of the three groups cannot be mentioned by only the Kruskal-Wallis test (p15, 243-248 line). Multiple comparison analysis is required to confirm these results.

Reply:

In this part, we showed the trend of the three groups' characteristics. Then, we performed multivariate ordered logit regression analysis including the related factors and identified the significantly related factors (Table 2). Since the aim was achieved, we did not perform that multiple comparison analysis.

Minor comments:

1. In Table 1, the interquartile range should be indicated by the 1st quartile – 3rd quartile. In addition, the authors should add the items such as pre-sarcopenia, sarcopenia etc in the column.

Reply:

I rewrote Table1 as you instructed. I had not written the items, robust, pre-sarcopenia, and sarcopenia; thus, I added them. Thank you for pointing this out.

2. I could not find the S1 and S2 tables in this revised version.

Reply:

In accordance with the PLOS one MANUSCRIPT BODY FORMATTING GUIDELINES, the S1 and S2 tables (supporting information) were uploaded in a separate file and were not included in the manuscript.

3. The median of age was 74.9 years in this manuscript. However, the mean age of the first manuscript was also 74.9 years. Is it correct?

Reply:

I made an error: mean age was exactly 74.89 years old and median age was 75.0 years old. I have corrected the text.

Attachment

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PLoS One. doi: 10.1371/journal.pone.0252784.r005

Decision Letter 2

Masaki Mogi

24 May 2021

An association analysis between hypertension, dementia, and depression and the phases of pre-sarcopenia to sarcopenia: A cross-sectional analysis

PONE-D-20-34154R2

Dear Dr. Endo,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Masaki Mogi

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #3: The revised version has been sufficiently addressed my concerns.

I would like to appreciate for the authors efforts.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: No

PLoS One. doi: 10.1371/journal.pone.0252784.r006

Acceptance letter

Masaki Mogi

13 Jul 2021

PONE-D-20-34154R2

An association analysis between hypertension, dementia, and depression and the phases of pre-sarcopenia to sarcopenia: A cross-sectional analysis

Dear Dr. Endo:

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Map showing the location of Dogo, which is one of the Oki Islands.

Published with permission from Oki Islands UNESCO Global Geopark Promotion Committee. Available from: http://www.oki-geopark.jp/en/features/ (accessed July 22, 2020).

(TIF)

Click here for additional data file.^{(943.8KB, tif)}

S1 Table. Mann-Whitney U test for the self-rating depression scale according to the presence of dementia (n = 753).

(TIFF)

Click here for additional data file.^{(182.4KB, tiff)}

S2 Table. Spearman’s rank correlations between the participants’ characteristics and sarcopenia-related factors.

* p < 0.10,** p < 0.05, *** p < 0.01.

(TIFF)

Click here for additional data file.^{(429.9KB, tiff)}

S3 Table. The number of participants who fell below the diagnostic criteria for sarcopenia was divided by sex and sub-category (pre-sarcopenia and sarcopenia).

(TIFF)

Click here for additional data file.^{(129.2KB, tiff)}

S1 Dataset

(XLSX)

Click here for additional data file.^{(140.9KB, xlsx)}

Attachment

Submitted filename: PLOSONE 20201208.docx

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Attachment

Submitted filename: Respons to Reviewers.docx

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Attachment

Submitted filename: Response_to_reviewers.docx

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Data Availability Statement

There are no ethical or legal restrictions on sharing a de-identified data set, which I uploaded as the additional file.

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PERMALINK

An association analysis between hypertension, dementia, and depression and the phases of pre-sarcopenia to sarcopenia: A cross-sectional analysis

Takeshi Endo

Kenju Akai

Tsunetaka Kijima

Shigetaka Kitahara

Takafumi Abe

Miwako Takeda

Toru Nabika

Shozo Yano

Minoru Isomura

Roles

Abstract

Introduction

Materials and methods

Participants

Fig 1. Flowchart of sampling of participants.

Design and ethical considerations

Measurement of anthropometry and skeletal muscle mass

Definition and classification of sarcopenia

Cognitive functions

Screening for depression

Screening for dementia

Covariates

Statistical analysis

Results

Table 1. Baseline characteristics of the study participants according to the presence of pre-sarcopenia and sarcopenia (n = 753).

Table 2. Multivariate ordered logit regression analysis for robust, pre-sarcopenia, and sarcopenia (n = 753).

Table 3. Multivariate logistic regression analysis between pre-sarcopenia and sarcopenia groups combined and robust.

Table 4. Multivariate logistic regression analysis between robust and pre-sarcopenia (n = 723).

Table 5. Multivariate logistic regression analysis between pre-sarcopenia (0) and sarcopenia (1) (n = 155).

Discussion

Limitations

Conclusion

Supporting information

Data Availability

Funding Statement

References

Decision Letter 0

Masaki Mogi

Roles

Author response to Decision Letter 0

Decision Letter 1

Masaki Mogi

Roles

Author response to Decision Letter 1

Decision Letter 2

Masaki Mogi

Roles

Acceptance letter

Masaki Mogi

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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