Gender differences in social-demographic factors associated with prefrailty in Japanese rural community-dwelling older adults

doi:10.21203/rs.3.rs-1610884/v1

Frailty in older adults is an important health issue. To prevent frailty, it is necessary to focus on prefrailty and consider preventive interventions that incorporate social aspects. This study investigated factors affecting prefrailty, focusing on social aspects.

A self-administered survey was conducted among residents aged ≥65 years in Japan. The survey assessed basic attributes, physical factors, mental factors, and social factors. The Kihon Checklist (KCL) was used to assess prefrailty. KCL scores were used to categorize participants into a prefrailty group and a healthy group. Logistic regression analysis was used to examine the relationship between prefrailty and scores for each gender.

Social factors significantly associated with prefrailty for women were social participation in middle age (odds ratio: 2.34, 95% confidence interval [CI]: 1.08–5.05, p=0.031) and having friends who listen to one’s concerns (odds ratio: 2.34, 95% CI: 1.03–5.32, p=0.043). However, no association with social factors was found for men.

This study showed that interventionable social factors that affected prefrailty in women were community involvement and being able to share concerns with friends. The findings suggest the need for support that emphasizes social aspects to prevent prefrailty. However, further research on social factors among men is warranted.

Frailty

Prefrailty

Social factors

Gender differences

Because of global population aging, frailty in older people has become one of the most important current health issues. Japan has the highest life expectancy in the world and has developed a national policy to address frailty. As part of this policy, frailty health checkups have been conducted in Japan since April 2020. Frailty is a multifactorial syndrome characterized by a decline in muscle strength, endurance, and physiological function, and increased vulnerability to negative health outcomes such as physical dysfunction and death [1]. Although the risk of frailty increases with age, the effects of frailty can be reversed with appropriate interventions [2]. Therefore, it is important to detect frailty at an early stage and provide necessary support to maintain and improve functionality.

Frailty is a multifaceted concept that includes mental, psychological, and social vulnerability as well as physical vulnerability [3]; therefore, efforts to address frailty should be multidimensional. However, most reports on the effectiveness of frailty prevention interventions have focused on the physical aspects, such as exercise and nutrition [4, 5]. Only a few reports have identified social factors that affect frailty, such as social networks, social support, social participation, and relationships with neighbors [6, 7, 8, 9]. Some previous studies have identified gender differences in frailty prevalence [10, 11] and factors that affect frailty [12] (including social factors), but to the best of our knowledge no studies have focused on frailty-associated social factors and associated gender-specific preventive interventions.

Because frailty is reversible, support aimed at recovery from frailty is important. However, it is equally important to prevent frailty from occurring in the first place. Frailty is characterized by a temporal continuum that involves the progression from a healthy state to prefrailty and then to frailty. Prefrailty is defined as a condition that predisposes to and usually precedes frailty [13]. Therefore, it is useful to focus on prefrailty, which is the stage before frailty, and to initiate timely interventions to prevent the transition to frailty. The prevalence of prefrailty is high among older people living in the community, indicating the need to focus not only on frailty but also on prefrailty [10]. Furthermore, it has been reported that the factors that affect improvement, and thus appropriate intervention methods, differ between frailty and prefrailty [7].

Given the reversibility of frailty, we believe that focusing on prefrailty and frailty prevention, taking into account gender differences, and conducting multifaceted research that includes both physical and social aspects could be useful in informing measures to prevent or improve the transition to frailty. Therefore, the purpose of this study was to examine possible factors that affect prefrailty with a focus on social aspects.

1. Research Design, Participants, and Methods

This was a cross-sectional study. The survey population was 900 stratified randomly selected residents of Nagatoro town, Saitama Prefecture, Japan, aged ≥ 65 years. Nagatoro has a population of 6,807 and an aging rate of 39.6%, compared with 28.6% for Japan as a whole [14]. Nagatoro is located in a basin surrounded by mountains. The survey participants were mailed a self-administered questionnaire. The survey period was from August to September 2021. To examine individual attributes associated with prefrailty, individuals judged as prefrail or healthy according to the frailty criteria described below were included in the analysis, and those judged as frail were excluded from the analysis.

2. Survey Items

1) Basic Attributes

The basic attributes of age and gender were determined.

2) Frailty

The Kihon Checklist (KCL) was used to assess frailty. The KCL was developed in Japan in 2006 [15] and has been validated to assess frailty [16]. The checklist has been translated into English [17], Portuguese [18], Spanish [19, 20], Chinese [21], Thai [22], Turkish [23], and other languages.

The KCL is a comprehensive assessment of frailty that comprises 25 questions on physical (motor function, nutritional status, oral function), mental (cognitive function, depressed mood), and social (being housebound) aspects and activities related to daily living. Possible responses on each item are 0 or 1; higher total scores (0–25) indicate more problems with daily functioning. The total score was used to determine frailty, with scores of ≥ 8 indicating frailty, 7–4 prefrailty, and ≤ 3 robustness [24]. As frailty includes physical, mental, and social factors, the KCL was selected because it is a multifactorial index.

3) Physical Aspects

Medical history, height, weight, regular exercise habits, and food intake status were ascertained. Body mass index (BMI kg/m² ) was calculated from height and weight, and a BMI of < 18.5 was defined as “thin.” Food intake status was determined using the Dietary variety score (DVS) [25] for 10 foods or food groups (seafood, meat, eggs, milk and dairy products, legumes, green and yellow vegetables, seaweed, potatoes, fruit, and oils and fats). Responses are a 4-point scale ranging from “eat every day” to “rarely eat,” with 1 point given for “eat every day” and 0 for all other responses. The total score ranges from 0 to 10.

4) Mental Aspects

Subjective health and depressive status [26] were assessed. Subjective health was measured on a 4-point scale ranging from “fairly healthy” to “not healthy.” The presence of depressive status was defined as a “yes” response to either the question “I feel down or depressed” or the question “I’m just not interested in things” during the last month.

5) Social Aspects

Household composition, employment status, economic status, frequency of going out, presence of intimate friends, community participation in middle age, social activities, solitary eating, and presence of friends who listen to one’s concerns were assessed.

3. Method of Analysis

Participants with KCL total scores of 4 to 7 were categorized as the prefrailty group and those with scores of ≤ 3 as the healthy group. Significant differences in basic attributes, and physical, mental, and social dimensions in the two groups by gender were confirmed using the chi-square test or Fisher’s exact test (for nominal variables) and the t-test (for continuous variables).

Next, odds ratios and 95% confidence intervals (CI) were calculated using logistic regression analysis with the presence or absence of prefrailty as the dependent variable. A univariable analysis was conducted in which each survey item was individually entered as an independent variable, and a multivariable analysis was conducted in which all independent variables were entered. The statistical package SAS ver9.4 (SAS Institute Inc., Cary, NC, USA) was used for statistical analysis, and the significance level was 5%.

4. Ethical considerations

The research was explained to the participants and their written informed consent was obtained. The study was approved by the ethics review committee of Teikyo University School of Medicine (Teirin 21–129). The study was carried out in accordance with relevant guidelines and regulations, including the Declaration of Helsinki and the ethical guidelines for epidemiological research, published in collaboration with the Ministry of Education, Culture, Sports, Science and Technology and the Ministry of Health, Labour and Welfare, Japan.

Of the 494 participants who returned questionnaires (54.9% response rate), 384 (203 men and 181 women) were included in the analysis. The analysis excluded one case with missing data for gender and age and 109 cases (32 men and 77 women) that were categorized as frail.

1. Comparison of prefrailty and healthy groups (Table 1)

Table 1

Comparison of Japanese community-dwelling older adults in prefrailty and healthy groups
			Male							Female
			Total		Prefrailty		Healthy		p	Total		Prefrailty		Healthy		p
			(n = 203)		(n = 93)		(n = 110)			(n = 181)		(n = 103)		(n = 78)
			n(%) or Mean/SD		n(%) or Mean/SD		n(%) or Mean/SD			n(%) or Mean/SD		n(%) or Mean/SD		n(%) or Mean/SD
Basic	Age(mean/SD)		74	/6	75	/6	74	/5	0.089	74	/6	75	/6	73	/5	0.019
Physical	DVS(mean/SD)		2.9	/2.4	2.6	/2.3	3.3	/2.4	0.075	3.9	/2.5	3.9	/2.7	3.8	/2.3	0.770
	Exercise habit	yes	153	(77)	65	(71)	88	(81)	1.000	146	(84)	81	(82)	65	(87)	0.513
		no	46	(23)	26	(29)	20	(19)		28	(16)	18	(18)	10	(13)
	Medical history	yes	40	(22)	19	(23)	21	(22)	0.295	37	(22)	16	(17)	21	(30)	0.064
		no	143	(78)	69	(77)	74	(78)		129	(78)	80	(83)	49	(70)
	BMI	~ 18.4	10	(5.0)	8	(8.7)	2	(1.9)	0.047	17	(10)	10	(10)	7	(9.9)	1.000
		18.5~	187	(95)	84	(91)	103	(98)		152	(90)	88	(90)	64	(90)
	Subjective symptoms	yes	109	(57)	44	(48)	65	(66)	0.015	106	(62)	51	(37)	55	(74)	0.005
		no	81	(43)	48	(52)	33	(34)		66	(38)	47	(63)	19	(26)
Mental	Depressive state	yes	31	(16)	22	(24)	9	(8.9)	0.007	46	(27)	34	(35)	12	(16)	0.007
		no	160	(84)	68	(76)	92	(91)		126	(73)	62	(65)	64	(84)
	Subjective health	good	177	(93)	78	(87)	99	(98)	0.006	156	(89)	84	(85)	72	(95)	0.066
		not-good	14	(7)	12	(13)	2	(1.9)		19	(11)	15	(15)	4	(5.3)
Social	Solitary living	yes	23	(11)	12	(13)	11	(10)	0.629	25	(14)	17	(17)	8	(10)	0.298
		no	178	(89)	79	(87)	99	(90)		154	(86)	84	(83)	70	(90)
	Solitary eating	no	162	(81)	71	(76)	91	(85)	0.166	139	(77)	73	(72)	66	(85)	0.059
		yes	38	(19)	22	(24)	16	(15)		41	(23)	29	(28)	12	(15)
	Job	yes	91	(45)	38	(41)	53	(48)	0.403	43	(24)	22	(22)	21	(28)	0.471
		no	111	(55)	54	(59)	57	(52)		134	(76)	79	(78)	55	(72)
	Economic status	difficult	55	(27)	31	(34)	24	(23)2	0.113	39	(22)	23	(23)	16	(21)	0.728
		usually	125	(62)	53	(58)	72	(65)		130	(73)	74	(73)	56	(73)
		afford	21	(11)	7	(7.7)	14	(12)		9	(5.1)	4	(3.9)	5	(6.4)
	Outings at least once a week	yes	189	(95)	88	(97)	101	(94)	0.511	173	(97)	97	(96)	76	(99)	0.391
	Outings at least once a week	no	9	(5)	3	(3.3)	6	(5.6)		5	(2.8)	4	(3.9)	1	(1.3)
	Intimate friend	yes	165	(85)	74	(82)	91	(87)	0.510	158	(91)	88	(89)	70	(93)	0.459
		no	30	(15)	16	(18)	14	(13)		16	(9.2)	11	(11)	5	(6.7)
	Being invited by someone	yes	91	(47)	42	(48)	49	(46)	0.949	106	(60)	55	(54)	51	(66)	0.152
	Being invited by someone	no	103	(53)	46	(52)	57	(54)		72	(40)	46	(46)	26	(34)
	Sources of Health Information	family and friend	106	(54)	46	(51)	60	(57)	0.532	118	(66)	62	(61)	56	(73)	0.154
	Sources of Health Information	otherwise	90	(46)	44	(49)	46	(43)		60	(34)	39	(39)	21	(27)
	Community participation at middle age	yes	117	(60)	49	(55)	68	(64)	0.252	102	(59)	49	(50)	53	(71)	0.010
	Community participation at middle age	no	78	(40)	40	(45)	38	(36)		71	(41)	49	(50)	22	(29)
	Participation in social activities at least once a week	yes	96	(49)	41	(45)	55	(53)	0.308	79	(47)	40	(43)	39	(52)	0.286
	Participation in social activities at least once a week	no	100	(51)	51	(55)	49	(47)		90	(53)	54	(57)	36	(48)
	Friends who listen to one's concerns	yes	60	(30)	30	(33)	30	(28)	0.495	102	(58)	53	(52)	49	(64)	0.148
	Friends who listen to one's concerns	no	140	(70)	61	(67)	79	(72)		75	(42)	48	(48)	27	(36)
	Listening to a friend's concerns	yes	64	(32)	31	(34)	33	(31)	0.667	102	(59)	54	(55)	48	(64)	0.272
	Listening to a friend's concerns	no	134	(68)	59	(66)	75	(69)		72	(41)	45	(45)	27	(36)
DVS: Dietary variety score; BMI: body mass index

1) Participant Characteristics

Based on the KCL scores, there were 93 (45.8%) men in the prefrailty group and 110 (54.2%) in the healthy group, and there were 103 (56.9%) women in the prefrailty group and 78 (43.1%) in the healthy group.

The mean (standard deviation) age was 75 (6) years for men in the prefrailty group and 74 (5) years in the healthy group, and 75 (6) years for women in the prefrailty group and 73 (5) years in the healthy group.

2) Physical Aspects

A significantly lower percentage of men in the healthy group had a BMI of < 18.5 (p = 0.047). The proportion of those who reported no subjective symptoms was significantly higher in the healthy group for both men and women (p = 0.015, p = 0.005).

3) Mental Aspects

For both men and women, a significantly lower percentage of those in the healthy group were classified as depressed (p = 0.007, p = 0.007). In addition, a significantly higher percentage of men in the healthy group reported better subjective health status (p = 0.006).

4) Social Aspects

A significantly lower percentage of women in the healthy group did not participate in community activities in middle age (p = 0.01). In contrast, no significant differences were found for men.

2. Factors associated with prefrailty

For men, the univariable analysis showed the following odds ratios: BMI < 18.5: 4.91 (95% CI: 1.01–23.72, p = 0.048); depression: 3.31 (95% CI: 1.43–7.63, p = 0.005); and subjective health status: 7.61 (95% CI: 1.66–35.0, p = 0.009). In the multivariable analysis with all items as independent variables, the odds ratios were as follows: BMI < 18.5: 13.05 (95% CI: 1.41–121.03, p = 0.024); DVS score: 0.81 (95% CI: 0.69–0.95, p = 0.011); and depression: 3.96 (95% CI: 1. 50–10.49, p = 0.006) (Table 2).

Table 2

Factors associated with prefrailty in Japanese rural community-dwelling older adults (men)
			Univariable			p	Multivariable		p
			n	OR	(95%CI)	p	OR	(95%CI)	p
Basic	Age
		65 ~ 74	108	1			1
		75~	95	1.22	(0.70–2.12)	0.484	1.49	(0.72–3.09)	0.283
Physical	BMI
		18.5~	187	1			1
		~ 18.4	10	4.91	(1.01–23.72)	0.048	13.05	(1.41-121.03)	0.024
	DVS		200	0.90	(0.79–1.01)	0.077	0.81	(0.69–0.95)	0.011
	Exercise habit
		yes	153	1			1
		no	46	1.76	(0.91–3.42)	0.096	1.83	(0.82–4.06)	0.140
Social	Solitary eating
		no	162	1			1
		yes	38	1.76	(0.86–3.60)	0.120	1.47	(0.58–3.72)	0.421
	Outings at least once a week
		yes	189	1			1
		no	9	0.57	(0.14–2.36)	0.442	0.54	(0.08–3.47)	0.515
	Community participation at middle age
		yes	117	1			1
		no	78	1.46	(0.82–2.60)	0.197	1.39	(0.67–2.86)	0.378
	Participation in social activities at least once a week
		yes	96	1			1
		no	100	1.4	(0.80–2.45)	0.246	1.08	(0.52–2.22)	0.840
	Friends who listen to one's concerns
		yes	60	1			1
		no	140	0.77	(0.42–1.42)	0.403	1.32	(0.62–2.84)	0.470
Mental	Depressive state
		no	160	1			1
		yes	31	3.31	(1.43–7.63)	0.005	3.96	(1.50-10.49)	0.006
	Subjective health
		good	177	1			1
		not-good	14	7.61	(1.66-35.00)	0.009	5.37	(0.91–31.79)	0.064
DVS: Dietary variety score; BMI: body mass index; OR: odds ratio; CI: confidence interval
The odds ratios in the univariable analysis were calculated for each explanatory variable.
The odds ratios in the multivariable analysis were calculated using a model that included all explanatory variables.

In contrast, for women, the univariable analysis showed the following odds ratios: age group > 75 years: 2.20 (95% CI: 1.20–4.05, p = 0.011); solitary eating: 2.18 (95% CI: 1.03–4.63, p = 0.041); community participation in middle age: 2.41 (95% CI: 1.28–4.55, p = 0.007); depression: 2.93 (95% CI: 1.39–6.16, p = 0.005); and subjective health status: 3.21 (95% CI: 1.02–10.12, p = 0.046). In the multivariable analysis, the odds ratios were as follows: community participation in middle age: 2.34 (95% CI: 1.08–5.05, p = 0.031); friends who listen to one’s concerns: 2.34 (95% CI: 1.03–5.32, p = 0.043); and depression 2.91 (95% CI: 1.19–7.09, p = 0.019) (Table 3).

Table 3

Factors associated with prefrailty in Japanese rural community-dwelling older adults (women)
			Univariable			p	Multivariable		p
			n	OR	(95%CI)	p	OR	(95%CI)	p
Basic	Age
		65 ~ 74	101	1			1
		75~	80	2.20	(1.20–4.05)	0.011	1.95	(0.87–4.37)	0.103
Physical	BMI
		18.5~	152	1			1
		~ 18.4	10	1.04	(0.38–2.88)	0.942	1.48	(0.46–4.81)	0.515
	DVS		178	1.02	(0.90–1.15)	0.775	1.12	(0.96–1.30)	0.158
	Exercise habit
		yes	146	1			1
		no	28	1.44	(0.62–3.34)	0.390	1.19	(0.40–3.53)	0.751
Social	Solitary eating
		no	139	1			1
		yes	41	2.18	(1.03–4.63)	0.041	1.80	(0.63–5.14)	0.270
	Outings at least once a week
		yes	173	1			1
		no	5	3.13	(0.34–28.62)	0.311	2.85	(0.17–47.59)	0.466
	Community participation at middle age
		yes	102	1			1
		no	71	2.41	(1.28–4.55)	0.007	2.34	(1.08–5.05)	0.031
	Participation in social activities at least once a week
		yes	79	1			1
		no	90	1.46	(0.79–2.69)	0.308	1.31	(0.62–2.77)	0.473
	Friends who listen to one's concerns
		yes	102	1			1
		no	75	1.64	(0.89–3.03)	0.111	2.34	(1.03–5.32)	0.043
Mental	Depressive state
		no	126	1			1
		yes	46	2.93	(1.39–6.16)	0.005	2.91	(1.19–7.09)	0.019
	Subjective health
		good	156	1			1
		not-good	19	3.21	(1.02–10.12)	0.046	1.15	(0.26–4.97)	0.856
DVS: Dietary variety score; BMI: body mass index; OR: odds ratio; CI: confidence interval
The odds ratios in the univariable analysis were calculated for each explanatory variable.
The odds ratios in the multivariable analysis were calculated using a model that included all explanatory variables.

This study focused on social-demographic factors and aimed to examine potential influencing factors for prefrailty. The analysis identified community participation in middle age and having friends who listened to one’s concerns as social factors that affected prefrailty in women. However, no association between social factors and prefrailty was found for men. Physical and psychological factors associated with frailty included thinness, DVS score, and depression for men, and depression for women.

Community participation in middle age and having friends who listened to one’s concerns, which were identified as socially relevant factors among women, were significantly associated with prefrailty even after adjusting for other factors such as age. These findings indicate that women who did not participate in the community in middle age and those with no friends with whom they could share their concerns were more likely to be categorized as prefrail.

There is evidence that individuals who participate in the community in middle age are more likely to join community activities after retirement because they possess many resources that are likely to lead to continued community participation; for example, they have familiar places of activity, and substantial experience in interacting with friends and acquaintances during community activities [27]. Older frail people have fewer opportunities to go out than healthy older people [28], and it may be difficult for them to find new opportunities to interact with local residents in older age. Although the present study did not identify a significant association between community participation and older age among men, research shows that men tend to be more work-oriented before older age than women and have less community involvement, making it difficult for them to participate in community activities after retiring from work [29]. Therefore, it is important to provide opportunities for both men and women to get involved with local residents before they reach older age, so that they can continue to be involved with the community during older age. Specifically a feasible intervention policy would be to revitalize existing venues for social activities and involve middle- to older-aged individuals in such activities.

Social support affects health and has been confirmed as having a positive effect on the health of older people, including an inhibiting effect on early death [30, 31, 32]. Social support includes emotional support and instrumental support; the availability of friends who listen to one’s concerns is an aspect of emotional support. Compared with men, women tend to have more close friends and to consult friends about their concerns [31, 32]. In addition, men’s social networks tend to be biased toward their spouses, whereas women’s social networks are more diverse and include children, other relatives, and friends [30]. In this study, we confirmed that men tend to have less emotional support than women. However, the effects of social and emotional support on frailty are unclear [6]. There is evidence for an association between emotional support and depression [33] and for an association between depression and frailty [34]. This suggests that social and emotional support may be associated with frailty, although it remains to be confirmed whether emotional support has a direct effect on prefrailty. We therefore also examined the effect of depression on prefrailty. However, we could not confirm this effect so further investigation is needed. However, research shows that many people experience a lack of companionship and trusted friends with age, and that elderly people living alone particularly lack emotional support [35]. A lack of social support is associated with depression; [35] therefore, individuals need a variety of ways in which they can acquire emotional support.

In this study, depression was associated with prefrailty for both men and women, which supports previous findings of an association between depression and frailty [34]. The present results are consistent with previous findings for men showing that thinness [36] and DVS scores [25, 37] are associated with frailty. The lack of these associations for women may be because health awareness and health consciousness tend to increase with age, particularly in women [38, 39]. Additionally, even women with prefrailty tend to practice healthy behaviors such as good eating habits and maintenance of an appropriate weight in accordance with such habits. This may explain the gender difference in the present study.

We considered the possibility that the relationship between the potential relevant factors examined here and prefrailty may differ according to the presence or absence of depression. However, we found no significant effect of depression.

The social factors solitary eating, going out more than once a week [40], and participating in social activities have been previously reported to affect frailty; however, these were not identified as relevant factors in the present study. This may be because few of our participants reported solitary eating or not going out more than once a week. In addition, participation in social activities can be affected by area of residence [8]; the geography of Nagatoro, which is surrounded by mountains, may therefore have affected participants’ social activities. Furthermore, there are many different types of social activities that have differing effects on health [41], so the type of activity engaged in needs to be considered. There may be other important social factors that were not investigated in this study; therefore, further research is needed to explore the effect of additional factors.

This study had several limitations. First, because this was a cross-sectional study, it was not possible to determine causal relationships between factors thought to affect prefrailty and its development. Longitudinal studies should be conducted to confirm causality. In particular, the possibility of reverse causality, in which unhealthy individuals are less likely to have social connections, has been reported [6], and further research on social factors is needed.

Second, we were not able to confirm whether the experience of community participation in participants’ middle age was linked to continued community participation in older age. Therefore, additional studies are needed to investigate the continuity of community participation.

Third, generalizability is limited because this study was conducted with older adults in one specific region, and regional characteristics may have affected the results. However, this is the first study to examine the possibility of preventive intervention from a social aspect, taking gender into account, and the findings may be useful for future studies of interventions to prevent or improve frailty.

This cross-sectional study of older adults showed that women identified community involvement in middle age and having friends who listened to their concerns as interventionable social factors that affected prefrailty. The findings suggest the need for support, with an emphasis on social aspects, to prevent frailty and prefrailty. In particular, it is important for individuals to have a variety of personal relationships that provide emotional support, and to develop community connections before older age. However, further research on social factors in men is needed.

Acknowledgments

We would like to express our sincere gratitude to the people of Nagatoro town for their cooperation in conducting this study.

This research was partially supported by the Taiyo Life Welfare Foundation.

We thank the professional English editing company Edanz for copy-editing and proofreading our manuscript.

Author contributions

All the authors contributed to the synthesis of the study design. A. Shibata created the questionnaire, and conducted data collection and analysis. A. Suzuki mainly contributed to the statistical analysis. K. Takahashi mainly contributed to the structure and synthesis of the manuscript.

All the authors read and approved the final version of the manuscript for publication.

Additional information

Competing interests

The authors declare no competing interests.

Data availability

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

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No competing interests reported.

Gender differences in social-demographic factors associated with prefrailty in Japanese rural community-dwelling older adults

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Version 1

Abstract

Introduction

Methods

Results

Discussion

Conclusion

Declarations

References

Additional Declarations

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Version 1