Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2021 May 27;16(5):e0252208. doi: 10.1371/journal.pone.0252208

Social capital and cognitive decline: Does sleep duration mediate the association?

Liqun Wang 1, Jiangping Li 1, Zhizhong Wang 2,*, Yong Du 3,4, Ting Sun 3, Li Na 3, Yang Niu 5,6,*
Editor: Y Zhan7
PMCID: PMC8158899  PMID: 34043692

Abstract

Background

Studies have found that social capital (SC) is associated with the risk of cognitive decline; however, the mechanism explaining how SC leads to cognitive decline is unclear. The current study examines the mediation effect of sleep duration on the relationship between SC and cognitive decline in Chinese older adults.

Methods

A cross-sectional study of 955 community-dwelling aged 60 or over was conducted. The mini-mental state examination (MMSE), self-report sleep duration questionnaire, and social capital scales were administered during the face-to-face survey. The Bootstrap methods PROCESS program is employed to test the mediation model.

Results

After controlling for covariates, both social cohesion and social interaction were positively correlated with the MMSE score (p<0.001), and social cohesion was negatively correlated with sleep duration (p = 0.009); On the contrary, sleep duration was negatively correlated with MMSE score (p<0.001). Linear regression analysis showed social cohesion was positively associated with the MMSE score (β = 0.16, p = 0.005), while sleep duration was associated with an increased risk of cognitive decline (β = -0.72, p<0.001). Sleep duration has mediated the relationship between social cohesion and cognitive decline (explaining 21.7% of the total variance).

Conclusions

Social capital negatively associated with the risk of cognitive decline in this Chinese population, and sleep duration may partly explain this relationship. It may be a suggestive clue to identify those at a higher risk of progressing to cognitive impairment. Further prospective study in need to confirm this finding due to the cross-sectional design.

Introduction

Expanded longevity is one of the most remarkable success stories in human history, and this also directs the population aging. The proportion of people aged 60 years and older is expected to rise to 22% of the total population in the coming decades, which is from 800 million to 2 billion [1]. One of the consequences of rapid population aging is the increased prevalence of aging-related diseases, of which dementia and mild cognitive impairment were the commonly prevalent neuropsychiatric disorders in older adults [2].

The determinants of cognitive decline include biological (Apolipoprotein E, protein tau, β-amyloid) and environmental factors (education, lifestyle, diet, medical service, social capital, etc.) [3–5]. Studies have also reported that sleep duration is an independent neurobehavioral predictor of cognitive disorders [6]. A meta-analysis suggested that longer sleep duration was associated with higher risks of mild cognitive impairment [7]. Another study revealed a U-shaped association that showed either shorter or longer sleep duration was associated with a higher risk of cognitive decline [8].

Social capital (SC) is a characteristic of social life, including interpersonal trust, norms of reciprocity, mutual aid, and social involvement (like socializing with friends, relatives, colleagues, or neighbors) [9], which has linked with several beneficial health outcomes [10, 11]. As a social determinant of health, SC may play an essential role in protecting individuals from cognitive decline. At least one study has found that SC accrued in early and midlife may reduce the detrimental influences of psychological stress on cognitive functioning in later life [12]. Specifically, possessing a rich SC (supportive personal network with numerous types of relationships, e.g., neighbor and friends) has been associated with better cognitive function among the old adults [13–17]. One possible explanation is individuals with rich SC lead to less life stress and more leisure time [12]. Also, one study found that poor SC might increase the risk of cognitive decline among elderly residents in Wuhan, China [18].

Besides, SC has been associated with sleep duration [19, 20]. A notable exception is one study that revealed an inverted U-shaped association between SC and sleep duration [19]. Takahashi et al. [21] reported that Japanese workers who had higher neighborhood or workplace social capital had a better quantity of sleep (not too short and too long).

There still unclear how SC leads to better cognitive function in older individuals. A previous study reported that shorter sleep duration mediated the association between homocysteine and cognitive decline [22]. They argued that short sleep duration might cause an increased homocysteine level, then strengthened Aβ accumulation, which is a critical pathological process of cognitive decline. The present study sought to examine the mediating effect of sleep duration on the relationship between SC and cognitive decline in old Chinese adults. We hypothesized that rich SC is associated with better cognitive function and that this association would be mediated at least in part by appropriate sleep duration.

Methods and materials

Study sample

Data were abstracted from a cross-sectional survey conducted from April 2017 to July 2017 at Ningxia province, China. The detailed sampling process can be found elsewhere [23]. Here, in summary, the participants were selected using a multi-stage sampling method: firstly, four counties were selected from a total of 22 counties in the province using a stratified sampling design according to the proportion of the minority population and the economic status. Secondly, twenty rural communities and twenty urban communities were selected among the four selected counties (with a total of 166 urban communities and 628 rural communities) using random sampling methods. Thirdly, 115 households were selected in each target communities using a systematic sampling method. Finally, one eligible family member from each household was determined to attend the survey using the Kish table. There were 615 households not responded after three times attempt to contact, and 3,985 eligible participants were finally selected. Of them, 1159 participants were aged 60 and over, and 104 participants were excluded due to the cognitive function test missing. Of them, 1159 participants were aged 60 and over, and 104 participants were excluded due to the cognitive function test’s missing value. Ultimately, 955 participants were included in this study (Fig 1). The inclusion criteria are a) living at the present address for at least six months and b) aged 60 years or older. The exclusion criteria were the following: a) unconsciousness caused by any forms; b) the acute phase of a cerebrovascular accident; c) a severe illness (e.g., stroke, cerebral infarction or myocardial infarction) that prevents communication; d) any obvious cognitive disabilities or deafness, aphasia or other language barriers; e) people reported with depression (by asking “do you ever be told have depression by your doctors”) and f) with sleep disorders and taking hypnotics or psychotropic medications, as well as some particular occupation need to going to bed late.

Fig 1. Participant screen process.

Fig 1

Open in a new tab

The Institutional Review Board of the General Hospital of Ningxia Medical University (approval number 2017–200) approved this study. All the participants provided a written consent form at the beginning of the survey.

The field process

The trained medical students served as investigators. With local community leaders’ cooperation, the investigators visited the participants’ houses to guide them to finish the survey, then described our study and questionnaire. Under the participants’ agreement, our investigators read the questions one by one to them and then recorded their answers, and the survey lasted approximately 45 minutes. As for respondents with low mini-mental state examination (MMSE) scores, other information is provided by family members. The finished questionnaire was double-checked immediately by a separate supervisor in the field.

Measurement

Cognitive function

The Chinese version of the MMSE scale was employed to assess the cognitive function, which has high sensitivity (90.8%) and specificity (93%) for screening cognitive disorders [24]. The MMSE consists of 19 questions to measure the five different domains of cognitive function (1) orientation, (2) memory, (3) attention and calculation, (4) language, and (5) constructional praxis (coping task, e.g. copying intersecting pentagons). And has a total score ranging from 0 to 30; a higher score reflects better cognitive function. We categorified cognitive performance into two categories (cognitive decline vs. normal according to Cui et al. suggested criteria [25]: MMSE ≤17 for those with no formal education; MMSE ≤ 20 for those with primary school education (≥6 years); and MMSE≤24 for those with junior high school education or above (≥ 9 years).

Social capital

SC was evaluated using the social capital scale to cover the two dimensions of social capital (social cohesion and social interaction) developed by Mujahid [26]. The social cohesion subscale consists of 4 items: 1) People around here are willing to help their neighbors, 2) People in my neighborhood generally get along with each other, 3) People in my neighborhood can be trusted, 4) People in my neighborhood share the same values. Each item ranged from 1 to 5 (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = strongly agree). Cronbach’s alpha was 0.88 among the Chinese sample [27], and among this sample was 0.81. The social interaction scale consists of five items: 1) You and other people in the community (village) help each other (e.g., look after children, help buy something and borrow tools), 2) When a neighbor is not at home or going out, you can help him look after the house or property, 3) people in the community (village) talk about each other’s personal matters (children care, exercise, etc.), 4) participate in group activities together with people in the community (village), and 5) communicate with each other on the street. Each item scored from 1 to 4 in response to a 4-point Likert scale (from never to often). The previous study has shown the Chinese version of the social interaction scale has good reliability and validity [27]. The Cronbach’s alpha in this sample was 0.76.

Sleep duration

Three questions “What time do you usually go to sleep at night?”, “What time do you usually rise in the morning?” and “In general, do you take afternoon nap often?”. The time between bedtime and rise up as the crude sleep duration, then it adjusted depends on the response to the question “In general, do you take afternoon nap often?” if the answer is yes, then the modified sleep duration is crude sleep duration plus one hour.

Socio-demographic information includes age, gender (male vs. female), ethnicity (Han vs. minority), residence (rural vs. urban), educational attainment (continuous data), marital status (married vs. unmarried/widowed/divorced), family income (as measured by the self-reported family average individual income per month and the answer included five groups: <1,000 RMB, 1,000–1,999 RMB, 2,000–2,999 RMB, 3,000–4,999 RMB, and 5,000 RMB or more) were collected using a standard form.

The data about body mass index (BMI = weight (kg)/height (m)2), fasting blood glucose (mmol/L), smoking (defined as at least one cigarette per day and last for six months or more), alcohol use (defined as a drink of at least one glass of alcohol, that equals 1/2 bottle of beer or 125-milliliter grape wine or fruit wine or 40-milliliter white wine, in a day for the past 12 months), hypertension (yes vs. no), dyslipidemia (yes vs. no) were abstracted from the medical record.

Statistical analyses

Analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 24.0 (IBM Inc., Chicago, Illinois, USA). We performed a logarithmic transformation of the MMSE score to fit the normal distribution. Means and standard deviations (SD) or were used to describe continuous variables; counts and proportions were used to describe categorical variables. The bivariate test using Student’s t-test or Chi-square test. Partial correlations were employed to create the correlation matrix under controlling the socio-demographic covariates. Three separate linear regression models were performed to examine the association among SC, sleep duration, and MMSE. In summary, model l include the SC and sleep duration; model 2 adjusted with covariate variables (age, gender, ethnicity, residence, educational attainment, marital status, family income, body mass index, smoking, alcohol use, fasting blood glucose, hyperlipidemia, hypertension); and the interaction between SC and sleep duration were added in model 3. And collinearity detected where the tolerance >0.1 and Variance Inflation Factor (VIF) <5 indicate multicollinearity can be ignored [28]. Bootstrap methods of PROCESS developed by Hayes was employed to test the mediation effect of sleep duration on the relationship between SC and MMSE score [29]. The bias-corrected percentile bootstrap confidence interval does not contain 0 indicate that the mediation effect statistically significant [30]. Sensitivity analyses were performed using Structural Equation Modelling (SEM) approach.

Results

Demographic characteristics of participants

The demographic characteristics of the participants were shown in Table 1. The average age was 66.9 (SD = 5.3) years, with a range of 60 to 80 years. Slightly about half (46.7%) were male, the mean educational attainment was 3.7 (SD = 4.2) years, and about 81.9% were married. The mean sleep duration was 8.1 (SD = 1.5) hours, the mean score of social cohesion was 15.7 (SD = 2.5), and for the social interaction was 13.2 (SD = 3.7). The mean score of MMSE was 23.6 (SD = 5.4). And the prevalence of cognitive decline (CD) was 15.8%. Participants with CD were older, more likely to have longer sleep duration, and lower SC scores than those with normal cognitive performance.

Table 1. Demographic characteristics of participants (n = 955).

Variables Total (N = 955) cognitive decline (N = 151) normal (N = 804) χ2/t p
Age, mean (SD), years 66.9(5.3) 68.7(5.8) 66.6(5.1) 4.08a <0.001
Gender, male, n (%) 446(46.7) 36(23.8) 410(51.0) 37.66 b <0.001
Ethnicity, han, n (%) 646(67.6) 109(72.2) 537(66.8) 2.83 b 0.243
Residence, rural, n (%) 479(50.2) 88(58.3) 391(48.6) 4.73 b 0.030
Marital status, n (%) 3.10 b 0.078
unmarried/widowed/divorced 173(18.1) 35(23.2) 138(17.2)
Married 782(81.9) 116(76.8) 666(82.8)
Educational attainment, mean (SD), years 3.7(4.2) 1.6(3.7) 4.0(4.1) 7.27 a <0.001
Family income, n (%) 37.95 b <0.001
<1000 RMB 505(52.9) 111(73.5) 394(49.0)
1000~1999 RMB 192(20.1) 17(11.2) 175(21.7)
2000~2999 RMB 148(15.5) 14(9.3) 134(16.7)
3000~4999 RMB 87(9.1) 6(4.0) 81(10.1)
≥5000 RMB 23(2.4) 3(2.0) 20(2.5)
Smoking, n (%) 181(19.0) 18(11.9) 163(20.3) 5.77 b 0.016
Alcohol use, n (%) 126(13.2) 5(3.3) 121(15.0) 15.29 b <0.001
BMI, mean (SD) 25.8(7.9) 25.5(4.0) 25.8(8.3) 0.44 a 0.662
FBG, mean (SD) 5.1(1.6) 5.0(1.4) 5.1(1.6) 0.53a 0.599
Hyperlipidemia, n (%) 38(4.0) 3(2.0) 35(4.4) 1.86 b 0.172
Hypertension, n (%) 385(40.3) 60(39.7) 325(40.4) 0.02 b 0.874
Social cohension, mean (SD) 15.7(2.5) 15.3(2.8) 15.7(2.5) 1.89 a 0.059
Social interaction, mean (SD) 13.2(3.7) 12.5(4.3) 13.3(3.6) 2.57 a 0.010
Sleep duration, mean (SD), hours 8.1(1.5) 9.0(1.6) 7.9(1.4) 7.58 a <0.001
Open in a new tab

SD: standard deviation; BMI: body mass index; FBG: fasting blood glucose

a: t-test used

b: chi-square test used.

The binary correlation matrix

The partial correlation matrix showed in Table 2. After controlling for socio-demographic variables (age, gender, ethnicity, residence, educational attainment, marital status, family income) and health variables (BMI, smoking, alcohol use, FBG, hyperlipidemia, hypertension), both the social cohesion (r = 0.12, P<0.001) and social interaction (r = 0.09, P<0.05) were positively correlated with MMSE score; the sleep duration was negatively correlated with MMSE score (r = -0.24, P<0.001); and the social cohesion was negatively correlated with sleep duration (r = -0.11, P = 0.003). As shown in Fig 2, a U-shaped association between sleep duration and MMSE score was found.

Table 2. Correlation matrix between SC, sleep duration, and MMSE score (n = 955)a.

Mean SD 1 2 3 4
1.MMSE 23.6 5.4 1
2.Social cohension 15.7 2.5 0.12** 1
3.Social interaction 13.2 3.7 0.09* 0.46** 1
4.Sleep duration 8.1 1.5 -0.24** -0.11* -0.05 1
Open in a new tab

**p<0.001

*p<0.05, SD = standard deviation

a: The covariates include age, gender, ethnicity, residence, educational attainment, marital status, family income, BMI, smoking, alcohol use, FBG, hyperlipidemia, hypertension were adjusted using Partial correlation method.

Fig 2. A U-shaped association between sleep duration and MMSE score.

Fig 2

Open in a new tab

Linear regression analysis

As Table 3 showed, social cohesion was positively associated with the MMSE score; namely, those with rich social cohesion may predict better cognitive performance. In contrast, sleep duration was inversely associated with the MMSE score (model 2). The same was true for social interaction. The association between SC and MMSE score disappeared when adding the interaction between SC and sleep duration (model 3), indicating that sleep duration is a possible mediator.

Table 3. Linear regression model for interaction between SC and sleep duration on cognitive decline (n = 955).

Variables Model 1 Model 2 Model 3
P value β (95%CI) P value β (95%CI) P value β (95%CI)
Social cohesion 0.192 0.09(-0.04,0.22) 0.005 0.16(0.05,0.27) 0.522 0.23(-0.39,0.84)
Sleep duration <0.001 -0.99(-1.21,-0.77) <0.001 -0.72(-0.91,-0.52) 0.311 -0.60(-1.75,0.55)
Social cohesion×sleep duration NA NA NA NA 0.900 -0.01(-0.08,0.07)
Social interaction 0.001 0.14(0.06, 0.23) 0.020 0.09(0.01,0.16) 0.607 0.11(-0.31,0.52)
Sleep duration <0.001 -0.98(-1.20,-0.76) <0.001 -0.74(-0.93,-0.54) 0.037 -0.71(-1.37,-0.05)
Social interaction×sleep duration NA NA NA NA 0.950 -0.01(-0.05,0.05)
Open in a new tab

Model l = SC+ sleep duration; Model 2 = Model l + covariate variables (age, gender, ethnicity, residence, educational attainment, marital status, family income, body mass index, smoking, alcohol use, fasting blood glucose, hyperlipidemia, hypertension); Model 3 = Model 2 + interaction between SC and sleep duration; Social interaction and social cohesion were tested separately in all the models. β: beta; 95%CI: 95% confidence interval; NA: not applicable.

R2 for social cohesion in model 1–3 are 0.081, 0.389, 0.389 respectively; R2 for social interaction in model 1–3 are 0.089, 0.388, 0.389 respectively.

Mediation effect of sleep duration on the relationship of SC and cognitive decline

As shown in Table 4, after controlling for covariates, there is a significant mediation effect of sleep duration on the relationship between social cohesion and cognitive decline. The results showed that both the direct effect (p = 0.004) and the indirect effect (p = 0.002) were significant. The mediation effect explained 21.7% (0.045/0.207) of the total variance. No mediation effect of sleep duration in the relationship between social interaction and cognitive decline was found.

Table 4. The mediating effect of sleep duration on the relationship between SC and cognitive decline *.

Effect Bias-Corrected 95%CI
β SE P-value Lower Upper
Social cohesion
Total effect 0.207 0.058 <0.001 0.093 0.332
Indirect Effects 0.045 0.016 0.002 0.018 0.082
Direct Effects 0.162 0.057 0.004 0.050 0.275
Social interaction
Total effect 0.104 0.039 0.007 0.026 0.181
Indirect Effects 0.004 0.002 0.133 -0.001 0.009
Direct Effects 0.090 0.038 0.019 0.015 0.165
Open in a new tab

*After controlling for age, gender, ethnicity, residence, educational attainment, marital status, family income, BMI, smoking, alcohol use, FBG, hyperlipidemia, hypertension.

Considering the possible U-shape relationship between sleep duration and cognitive decline, the exploring analysis conducted stratified (use a cutoff point of mean sleep duration of the total sample) by sleep duration showed in Table 5. The mediation effect of sleep duration on the relationship between social cohesion and cognitive decline persists in those who had eight hours and longer sleep duration. However, the mediation effect disappears in those who had less than eight hours of sleep duration per day.

Table 5. The mediation model of social cohesion stratified by sleep durationa.

Effect Bias-Corrected 95%CI
β SE P-value Lower Upper
sleep duration <8 h
Total effect 0.196 0.093 0.038 0.011 0.380
Indirect Effects -0.001 0.008 0.954 -0.012 0.022
Direct Effects 0.197 0.093 0.038 0.011 0.380
sleep duration ≥8 h
Total effect 0.164 0.074 0.026 0.019 0.309
Indirect Effects 0.041 0.021 0.025 0.008 0.091
Direct Effects 0.123 0.072 0.089 -0.019 0.265
Open in a new tab

a: The effect adjusted the covariates include age, gender, ethnicity, residence, educational attainment, marital status, family income, BMI, smoking, alcohol use, FBG, hyperlipidemia, hypertension.

Sensitivity analysis

As showed in Fig 3, the SEM approach was peformed to sensitivity analysis. The results showed social cohension was positively associated with cognitive function and inversely related to sleep duration, and sleep duration negatively associated with cognitive function. These results was consistent with the binary correlation results even though the pathway coefficient was not the same due to the different methods. This validated the methodological robustness of findings.

Fig 3.

Fig 3

Open in a new tab

Discussion

The current study examined the association between SC and cognitive decline. And provides the primary evidence for the relationship between SC and cognitive decline among older adults, suggesting a possible mechanism to explain how SC is related to reduce cognitive impairment in studies examining that association. As hypothesized, the results revealed a positive association of SC with cognitive performance in older Chinese adults, and this relationship was partially mediated by sleep duration. The mediation effect is accounting for 21.7% of the total effect in the total sample, while no mediation effect was found among those who had less than eight hours of sleep duration.

Sleep duration was negatively associated with MMSE. Long sleep duration might be a risk factor for cognitive decline, consistent with prior research that found long sleep duration was associated with cognitive impairment [31–33]. A cohort study found long sleep duration was associated with poorer cognitive performance among adults aged 41–75 years [34]. Previous studies also have reported that long sleep duration is associated with low MMSE scores among old adults [35–39]. One possible explanation is increased sleep fragmentation associated with decreased cognitive performance, and so it may be that longer sleep duration may emerge more frequent nighttime wakes or sleep in bed much more time [40]. Additionally, obstructive sleep apnea syndrome (OSAS) can cause deterioration in cognitive functions, and the study reported that OSAS was more prevalent in extended sleep duration groups [41, 42]. Besides, long sleep duration has been associated with an increased level of inflammatory factors [43, 44], and elevated inflammatory cytokine levels increase the risk of cognitive decline [45]. Furthermore, reports revealed a U-shaped association with a higher risk of cognitive decline in older adults with either short or long sleep duration [7, 46, 47].

Compared with lower SC, the average sleep duration was shorter in those who have higher SC. This finding was consistent with the previous study that found lower neighborhood SC was negatively associated with short sleep duration among Japanese male adults [17]. China is a typical Guanxi-based society, and the previous study has reported that Guanxi (traditional Chinese social interaction) has almost the same connotation as social capital [48]. Additionally, rural China’s culture values trust, mutual assistance, and reciprocal exchange, which provide cultural soil for cultivating social capital [49].

The current study also found SC was positively correlated with the MMSE score and might be a protective factor of cognitive function. One study conducted in Taiwan revealed that increased social support is associated with better cognitive function in older adults [50]. Also, Holtzman and his colleagues reported a positive association between social support and cognitive function among older adults [51]. Moreover, a three-year cohort study found that social networks reduced the incidence of dementia in older adults [52]. On the one hand, the possible mechanisms were social activities provide the challenge of effective communication and participation in complex interpersonal exchanges [53]. On the other hand, emotional support might buffer against physiological stress and benefit cognitive function [54]. Furthermore, a recent study manifested that social capital could help older adults continue to independently live in local communities and handle life stressors efficiently, even when they encounter declines in their physical and cognitive health. Social capital can provide older residents with a sense of security and belonging and is an important reserve domain in old age [55].

Strength and limitations

Given the increasing rate of aging and the incidence of dementia in the elderly Chinese population, the present findings have relevance for understanding the mechanisms of how SC is linked with cognitive function. And provide primary evidence for developing interventional program for cognitive decline in minority areas. Several limitations were identified; first, the cross-sectional design prevents making causal inferences from the relationships between SC and cognitive decline reported here. Hence, further longitudinal design would be necessary to determine causal relationships in the future. Second, potential confounding variables like depression that were not included in the analysis may lead to overestimation of the association between cognitive function and sleep duration. Third, due to the feasibility consideration, bedtime and sleep duration were collected via a self-reported survey question; it may involve information bias even though it has been found to have a reasonable correlation with actigraphic measurement [56].

Conclusions

Social cohesion, one dimension of the social capital, positively associated with cognitive function, and sleep duration partly mediated this relationship. The findings provides the primary evidence for better understanding how SC is related to reduce risk of cognitive decline in studies examining that association. Hence, clinicians can suggest patients communicate more with others (chat, play chess or exercise together, etc.) to improve the social capital, and in turn maintain their cognitive function.

Supporting information

S1 Data

(SAV)

Click here for additional data file. (123.6KB, sav)

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The study was supported by the Research and Development Plan of the 13th five-year plan of Ningxia autonomous region (the major S&T projects.) (grant number 2016BZ02) and the National Natural Science Foundation of China (grant number 81860599).

References

  • 1.Bloom DE, Chatterji S, Kowal P, Lloyd-Sherlock P, McKee M, Rechel B, et al. Macroeconomic implications of population ageing and selected policy responses. Lancet. 2015; 385: 649–657. 10.1016/S0140-6736(14)61464-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.World Health Organization. Dementia: a public health priority. http://www.who.int/mental_health/publications/demeatia_report_2012/en/
  • 3.Wang LQ, Wang ZZ, Koenig HG, Alshohaib S. Interactions between Apolipoprotein E Genes and Religiosity in Relation to Mild Cognitive Impairment. Neuropsychiatry. 2017; 07: 659–666. 10.4172/Neuropsychiatry.1000262 [DOI] [Google Scholar]
  • 4.Buerger K, Teipel SJ, Zinkowski R, Blennow K, Arai H, Engel R, et al. CSF tau protein phosphorylated at threonine 231 correlates with cognitive decline in MCI subjects. Neurology. 2002; 59: 627–629. 10.1212/wnl.59.4.627 [DOI] [PubMed] [Google Scholar]
  • 5.Li X, Ma C, Zhang J, Liang Y, Chen Y, Chen K, et al. Prevalence of and potential risk factors for mild cognitive impairment in community-dwelling residents of Beijing. J Am Geriatr Soc. 2013; 61: 2111–2119. 10.1111/jgs.12552 [DOI] [PubMed] [Google Scholar]
  • 6.Chen JC, Espeland MA, Brunner RL, Lovato LC, Wallace RB, Leng X, et al. Sleep duration, cognitive decline, and dementia risk in older women. Alzheimers Dement. 2016; 12: 21–33. 10.1016/j.jalz.2015.03.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Liang Y, Qu LB, Liu H. Non-linear associations between sleep duration and the risks of mild cognitive impairment/dementia and cognitive decline: a dose-response meta-analysis of observational studies. Aging Clin Exp Res. 2019; 31: 309–320. 10.1007/s40520-018-1005-y [DOI] [PubMed] [Google Scholar]
  • 8.Wu L, Sun DL, Tan Y. A systematic review and dose-response meta-analysis of sleep duration and the occurrence of cognitive disorders. Sleep Breath. 2018; 22: 805–814. 10.1007/s11325-017-1527-0 [DOI] [PubMed] [Google Scholar]
  • 9.Kawachi I, Kim D, Coutts A, Subramanian SV. Commentary: Reconciling the three accounts of social capital. Int J Epidemiol. 2004; 33: 682–690. 10.1093/ije/dyh177 [DOI] [PubMed] [Google Scholar]
  • 10.Verhaeghe PP and Tampubolon G. Individual social capital, neighbourhood deprivation, and self-rated health in England. social science & medicine. 2012; 75: 349–357. 10.1016/j.socscimed.2012.02.057 [DOI] [PubMed] [Google Scholar]
  • 11.Ziersch AM. Health implications of access to social capital: findings from an Australian study. Social Science & Medicine. 2005; 61: 2119–2131. 10.1016/j.socscimed.2005.01.015 [DOI] [PubMed] [Google Scholar]
  • 12.Ihle A, Oris M, Sauter J, Rimmele U, Kliegel M. Cognitive Reserve and Social Capital Accrued in Early and Midlife Moderate the Relation of Psychological Stress to Cognitive Performance in Old Age. Dement Geriatr Cogn Disord. 2018; 45: 190–197. 10.1159/000488052 [DOI] [PubMed] [Google Scholar]
  • 13.Bennett DA, Schneider JA, Tang Y, Arnold SE, Wilson RS. The effect of social networks on the relation between Alzheimer’s disease pathology and level of cognitive function in old people: a longitudinal cohort study. Lancet Neurol. 2006; 5: 406–412. 10.1016/S1474-4422(06)70417-3 [DOI] [PubMed] [Google Scholar]
  • 14.Crooks VC, Lubben J, Petitti DB, Little D, Chiu V. Social network, cognitive function, and dementia incidence among elderly women. Am J Public Health. 2008; 98: 1221–1227. 10.2105/AJPH.2007.115923 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Ellwardt L, Van Tilburg TG, Aartsen MJ. The mix matters: Complex personal networks relate to higher cognitive functioning in old age. Soc Sci Med. 2015; 125: 107–115. 10.1016/j.socscimed.2014.05.007 [DOI] [PubMed] [Google Scholar]
  • 16.Kimura D, Takeda T, Ohura T, Imai A. Evaluation of facilitative factors for preventing cognitive decline: A 3-year cohort study of community intervention. Psychogeriatrics. 2016; 17: 9–16. 10.1111/psyg.12182 [DOI] [PubMed] [Google Scholar]
  • 17.Wang B, He P, Dong B. Associations between social networks, social contacts, and cognitive function among Chinese nonagenarians/centenarians. Arch Gerontol Geriatr. 2015; 60: 522–527. 10.1016/j.archger.2015.01.002 [DOI] [PubMed] [Google Scholar]
  • 18.Wang C, Zhu J, Cai Y, Cui D, Wang Q, Mao Z. Community-Based Study of the Relationship Between Social Capital and Cognitive Function in Wuhan, China. Asia Pac J Public Health. 2016; 28: 717–724. 10.1177/1010539516640351 [DOI] [PubMed] [Google Scholar]
  • 19.Win T, Yamazaki T, Kanda K, Tajima K, Sokejima S. Neighborhood social capital and sleep duration: a population based cross-sectional study in a rural Japanese town. BMC Public Health. 2018; 18: 343. 10.1186/s12889-018-5204-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Cheng GH, Chan A, Lo JC. Importance of social relationships in the association between sleep duration and cognitive function: data from community-dwelling older Singaporeans. Int Psychogeriatr. 2018; 30: 893–901. 10.1017/S1041610217001041 [DOI] [PubMed] [Google Scholar]
  • 21.Takahashi M, Tsutsumi A, Kurioka S, Inoue A, Shimazu A, Kosugi Y, Kawakami N. Occupational and socioeconomic differences in actigraphically measured sleep. J Sleep Res. 2014; 23: 458–462. 10.1111/jsr.12136 [DOI] [PubMed] [Google Scholar]
  • 22.Sanchez-Espinosa MP, Atienza M, Cantero JL. Sleep mediates the association between homocysteine and oxidative status in mild cognitive impairment. Sci Rep. 2017; 7: 7719. 10.1038/s41598-017-08292-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Wang L, Li J, Du Y, Sun T, Na L, Wang Z. The relationship between sleep onset time and cardiometabolic biomarkers in Chinese communities: a cross-sectional study. BMC Public Health. 2020; 20:374. 10.1186/s12889-020-08516-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Zhang ZX, Zahner GE, Román GC, Liu XH, Wu CB, Hong Z, et al. Socio-demographic variation of dementia subtypes in china: Methodology and results of a prevalence study in Beijing, Chengdu, Shanghai, and Xian. Neuroepidemiology. 2006; 27: 177–187. 10.1159/000096131 [DOI] [PubMed] [Google Scholar]
  • 25.Cui GH, Yao YH, Xu RF, Tang HD, Jiang GX, Wang Y, et al. Cognitive impairment using education-based cutoff points for CMMSE scores in elderly Chinese people of agricultural and rural Shanghai China. Acta Neurol Scand. 2011; 124: 361–367. 10.1111/j.1600-0404.2010.01484.x [DOI] [PubMed] [Google Scholar]
  • 26.Mujahid MS, Diez Roux AV, Morenoff JD, Raghunathan T. Assessing the measurement properties of neighborhood scales: from psychometrics to ecometrics. Am J Epidemiol. 2007; 165: 858–867. 10.1093/aje/kwm040 [DOI] [PubMed] [Google Scholar]
  • 27.Gao J, Fu H, Li J, Jia Y. Association between social and built environments and leisure-time physical activity among Chinese older adults: a multilevel analysis. BMC Public Health. 2015; 15:1–11. 10.1186/1471-2458-15-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Mason Charlotte H, Perreault William D. Collinearity, Power, and Interpretation of Multiple Regression Analysis. Journal of Marketing Research. 1991; 28: 268–280. [Google Scholar]
  • 29.Hayes A. Introduction to mediation, moderation, and conditional process analysis. Journal of Educational Measurement. 2013; 51: 335–337. [Google Scholar]
  • 30.MacKinnon DP, Fritz MS, Williams J, Lockwood CM. Distribution of the product confidence limits for the indirect effect: Program PRODCLIN. Behav Res Methods. 2007; 39: 384–389. 10.3758/bf03193007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Schmutte T, Harris S, Levin R, Zweig R, Katz M, Lipton R. The relation between cognitive functioning and self-reported sleep complaints in nondemented older adults: results from the Bronx aging study. Behav Sleep Med. 2007; 5: 39–56. 10.1207/s15402010bsm0501_3 [DOI] [PubMed] [Google Scholar]
  • 32.Loerbroks A, Debling D, Amelang M, Stürmer T. Nocturnal sleep duration and cognitive impairment in a population-based study of older adults. Int J Geriatr Psychiatry. 2010; 25: 100–109. 10.1002/gps.2305 [DOI] [PubMed] [Google Scholar]
  • 33.Malek-Ahmadi M, Kora K, O’Connor K, Schofield S, Coon D, Nieri W. Longer self-reported sleep duration is associated with decreased performance on the montreal cognitive assessment in older adults. Aging Clin Exp Res. 2015; 28: 333–337. 10.1007/s40520-015-0388-2 [DOI] [PubMed] [Google Scholar]
  • 34.van Oostrom SH, Nooyens ACJ, van Boxtel MPJ, Verschuren WMM. Long sleep duration is associated with lower cognitive function among middle-age adults-the Doetinchem Cohort Study. Sleep Med. 2018; 41: 78–85. 10.1016/j.sleep.2017.07.029 [DOI] [PubMed] [Google Scholar]
  • 35.Ramos AR, Dong C, Elkind MS, Boden-Albala B, Sacco RL, undek T, et al. Association between sleep duration and the mini-mental score: the Northern Manhattan study. J Clin Sleep Med. 2013; 9: 669–673. 10.5664/jcsm.2834 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Auyeung TW, Lee JS, Leung J, Kwok T, Leung PC, Woo J, et al. Cognitive deficit is associated with phase advance of sleep-wake rhythm, daily napping, and prolonged sleep duration-a cross-sectional study in 2,947 community-dwelling older adults. Age. 2013; 35: 479–486. 10.1007/s11357-011-9366-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Virta JJ, Heikkilä K, Perola M, Koskenvuo M, Räihä I, Rinne JO, et al. Midlife sleep characteristics associated with late life cognitive function. Sleep. 2013; 36: 1533–1541. 10.5665/sleep.3052 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Benito-León J, Louis ED, Bermejo-Pareja F. Cognitive decline in short and long sleepers: A prospective population-based study (NEDICES). J Psychiatr Res. 2013; 47: 1998–2003. 10.1016/j.jpsychires.2013.09.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Faubel R, López-García E, Guallar-Castillón P, Graciani A, Banegas J R, Rodríguez-Artalejo F. Usual sleep duration and cognitive function in older adults in Spain. J Sleep Res. 2010; 18: 427–435. 10.1111/j.1365-2869.2009.00759.x [DOI] [PubMed] [Google Scholar]
  • 40.Blackwell T, Yaffe K, Ancoli-Israel S, Redline S, Ensrud KE, Stefanick ML, et al. association of sleep characteristics and cognition in older community-dwelling men: the MrOS sleep study. Sleep. 2011; 34: 1347–1356. 10.5665/SLEEP.1276 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Bliwise DL, King AC, Harris RB. Habitual sleep durations and health in a 50–65 year old population. J Clin Epidemiol. 1994; 47: 35–41. 10.1016/0895-4356(94)90031-0 [DOI] [PubMed] [Google Scholar]
  • 42.Bédard MA, Montplaisir J, Richer F, Rouleau I, Malo J. Obstructive Sleep Apnea Syndrome: Pathogenesis of Neuropsychological Deficits. J Clin Exp Neuropsychol. 1991; 13: 950–964. 10.1080/01688639108405110 [DOI] [PubMed] [Google Scholar]
  • 43.Grandner MA, Buxton OM, Jackson N, Sands-Lincoln m, Pandey A, Jean-Louis G. Extreme sleep durations and increased C-reactive protein: effects of sex and ethnoracial group. Sleep. 2013; 36:769–779. 10.5665/sleep.2646 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Patel SR, Zhu X, Storfer-Isser A, Mehra R, Jenny NS, Tracy R, et al. Sleep duration and biomarkers of inflammation. Sleep. 2009; 32:200–204. 10.1093/sleep/32.2.200 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Windham BG, Simpson BN, Lirette S, Bridges J, Bielak L, Peyser PA, et al. Associations Between Inflammation and Cognitive Function in African Americans and European Americans. Journal of the American Geriatrics Society. 2014; 62: 2303–2310. 10.1111/jgs.13165 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Xu L, Jiang CQ, Lam TH, Liu B, Jin YL, Zhu T, et al. Short or long sleep duration is associated with memory impairment in older Chinese: the Guangzhou Biobank Cohort Study. Sleep. 2011; 34: 575–580. 10.1093/sleep/34.5.575 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Song QF, Liu XX, Hu WN, Han XC, Zhou WH, Lu AD, et al. Night Sleep Duration and Risk of Cognitive Impairment in a Chinese Population: A Cross-sectional Study. Biomed Environ Sci. 2017; 30: 749–757. 10.3967/bes2017.100 [DOI] [PubMed] [Google Scholar]
  • 48.Bian Y. Bringing strong ties back in: Indirect ties, network bridges, and job searches in China. American Sociological Review. 1997; 62: 366–385. 10.2307/2657311 [DOI] [Google Scholar]
  • 49.Hang L, Zhang Y, Erpeng L, Nan X. How does social capital affect individual health among the elderly in rural China?—Mediating effect analysis of physical exercise and positive attitude. PloS One. 2020; 15: e0231318. 10.1371/journal.pone.0231318 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Yeh SC, Liu YY. Influence of social support on cognitive function in the elderly. BMC Health Serv Res. 2003; 3: 9. 10.1186/1472-6963-3-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Holtzman RE, Rebok GW, Saczynski JS, Kouzis AC, Wilcox Doyle K, Eaton WW. Social network characteristics and cognition in middle-aged and older adults. J Gerontol B Psychol Sci Soc Sci. 2004; 59: P278–284. 10.1093/geronb/59.6.p278 [DOI] [PubMed] [Google Scholar]
  • 52.Fratiglioni L, Wang HX, Ericsson K, Maytan M, Winblad B. Influence of social network on occurrence of dementia: a community-based longitudinal study. Lancet. 2000; 355: 1315–1319. 10.1016/S0140-6736(00)02113-9 [DOI] [PubMed] [Google Scholar]
  • 53.Berkman LF. Which influences cognitive function: living alone or being alone? Lancet. 2000; 355: 1291–1292. 10.1016/S0140-6736(00)02107-3 [DOI] [PubMed] [Google Scholar]
  • 54.Uchino BN, Holt-Lunstad J, Uno D, Betancourt R, Garvey TS. Social support and age-related differences in cardiovascular function: An examination of potential mediators. Ann Behav Med. 1999; 21: 135–142. 10.1007/BF02908294 [DOI] [PubMed] [Google Scholar]
  • 55.Zhang J, Lu N, Wang W. Does Education Moderate the Relationship between Social Capital and Cognitive Function among Older Adults? Evidence from Suzhou City, China. Int J Environ Res Public Health. 2020;17:6560. 10.3390/ijerph17186560 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Lockley S W, Skene D J, Arendt J. Comparison between subjective and actigraphic measurement of sleep and sleep rhythms. Journal of Sleep Research. 1999; 8:175–183. 10.1046/j.1365-2869.1999.00155.x [DOI] [PubMed] [Google Scholar]

Decision Letter 0

Enrico Mossello

11 Dec 2020

PONE-D-20-28198

Social capital and cognitive decline: does sleep duration mediate the association?

PLOS ONE

Dear Dr. Wang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

In agreement with suggestions of Reviewer 2 I feel that the analysis, and possibly the message, of the paper should undergo a really major revision, as present conclusions seem to have limited support from data.

In fact the main message of the paper is that social capital is associated with the risk of cognitive decline. Yet correlations between measures of SC and MMSE are small. Social cohesion has a correlation of .12, while social interaction has a correlation of 0.09. Moreover based on Table 3, it looks like social cohesion is not associated with MMSE in univariate analysis.

The whole hypothesis of the mediation is made uncertain by the cross-sectional design. In fact both low social capital and longer sleep duration might be consequence, rather than predictors, of cognitive decline. In fact the present message of the paper would be that older subjects should sleep less to maintain their social capital, that seems at odds with evidence suggesting an association between shorter sleep time and increased risk of cognitive decline.

As further statistical suggestion, MMSE distribution is probably non-normal. It would be probably better to categorize it and perform a multinomial regression instead of a linear regression analysis. It would be of interest to include in the same model as predictors social capital, sleep time and interaction between the two factors.

Please submit your revised manuscript by 23-JAN-2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Enrico Mossello

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. PLOS requires an ORCID iD for the corresponding author in Editorial Manager on papers submitted after December 6th, 2016. Please ensure that you have an ORCID iD and that it is validated in Editorial Manager. To do this, go to ‘Update my Information’ (in the upper left-hand corner of the main menu), and click on the Fetch/Validate link next to the ORCID field. This will take you to the ORCID site and allow you to create a new iD or authenticate a pre-existing iD in Editorial Manager. Please see the following video for instructions on linking an ORCID iD to your Editorial Manager account: https://www.youtube.com/watch?v=_xcclfuvtxQ

3.Thank you for stating the following in the Funding Section of your manuscript:

[The study was supported by the Research and Development Plan of the 13th five-year plan of

Ningxia autonomous region (the major S&T projects.) (grant number 2016BZ02) and the

National Natural Science Foundation of China (grant number 81860599).]

We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form.

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

 [The author(s) received no specific funding for this work.]

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

4. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Partly

**********

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

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: No

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This study aimed to examine the sleep duration involvement on the positive association between SC and cognitive functioning in aged people. The topic is quite interesting and study design, writing and formatting are well done. Only some points and issues come to my mind as following:

Introduction

Overlay, this section has been prepared orderly. In the last paragraph, authors want to point the relationship between sleep duration and cognitive functions and properly reference to the study which conclude that homocysteine and beta amyloid may mediate the effects of poor sleep on cognition. However, ref 22 (smoking and sleep) here is not related to the main issue and I think it should be removed and instead another relevant ref can be added.

Methods

Line 133:the fifth domain of MMSE is vague. Please refine it.

Sleep duration: I am wondering why the authors did not consider the sleep quality rather than sleep duration. Then, they could easily use the well-known and standard scale, Pittsburgh sleep questionnaire.

Discussion: in the second paragraph which deals with the association between sleep duration and cognition, authors remark the sleep fragmentation and OSA as the possible causations of long sleep duration and low MMSE scales. But, I can’t understand why the authors mention here to the short sleep duration as this is a very definite and old finding and also they have no data on this issue. Rather, more relevant findings regarding the physiological alteration associated with long sleep duration could be of most benefits.

the last paragraph regarding the positive correlation of SC and MMSE scores could be discussed more deeply with mentioning to the some relevant basic findings.

The whole manuscript should be proof read for some grammatical and spelling errors. The example is in Line 210: there no!

Reviewer #2: The article by Wang et al. examines the association between social capital, sleep, and cognitive decline in a sample of older (age > 60 years) adults. Using self-report data, they measure cognitive decline, social capital (via scales measuring social cohesion and social interaction), and sleep duration. Upon conducting a mediation analysis on these variables, they suggest that sleep duration may mediate the connection between social cohesion and cognitive decline. Their study further highlights potential issues both with longer sleep duration and shorter sleep duration.

This is an important topic to investigate, given the increasing evidence supporting a connection between sleep and cognitive impairment in older individuals. Social factors can play a role both in overall physical and mental health. Thus, their connection to the association between sleep and cognitive decline is important to understand. While the overall topic of the article has merit, there are some issues:

Minor issues:

• There are several issues with the overall writing style and appropriate use of grammar. This issue extends throughout the article.

• On line 125, “MMSE” is used for the first time in the text of the article, though the acronym is not explained until the following paragraph. Acronyms should be spelled out upon their first use. This made understanding line 125 a bit difficult.

• Further, the explanation of how the MMSE is scored in the Method section is a bit tricky to decipher. It is unclear if lower scores translate to cognitive impairment, or if higher scores do. This will help with understanding the beginning of the discussion section where the results are summarized.

• On line 194, no r values are given for the association between social cohesion/interaction and MMSE. Only one p-value is provided here.

• On line 221, the author states “SC leads to better cognitive performance…” However, this study cannot provide any causal interpretations of the data since there was no manipulation of variables.

• On line 222, the author states that SC is negatively associated with risk of cognitive decline, but the correlations between social cohesion/interaction and MMSE were positive. Further, on line 251, the author then states that SC is positively correlated with MMSE. These statements should be edited so that they agree with the data.

• In the results, it was unclear why analyses were done both with those who slept less than 8 hours and those who slept 8 hours +. Perhaps a brief discussion of this in the methods or in the results section would help the reader better understand this analysis.

• The paragraph starting on line 226 seems to be making the point that there is evidence that both long and short sleep are connected to cognitive decline. However, the language pointing to this conclusion seems to be a little vague in this paragraph. Specifically, there is a sudden jump from talking about evidence about longer sleep duration to shorter sleep duration. A transition word or sentence might help to bridge this gap and clarify the overall point of this paragraph.

• The paragraph starting on line 242 seems to have a similar issue. The point here appears to be that people with more social capital are busier, and thus are getting less sleep, but this point again seems to be vague and somewhat difficult for the reader to decipher.

Major issues:

• The measurement of sleep duration appears to be problematic. Specifically, I’m not sure how appropriate it is to simply add 1 hour to the overall calculated sleep duration if someone answers “yes” to the question about whether they napped. Ideally, a follow-up question could have asked respondents who indicated napping how long they were asleep during the nap. This kind of information is fairly easy to record, so it is unclear why that was not originally built into the design.

• The measurement of alcohol use seems a bit unclear. Based on the article, it appears that this might have been a yes/no measurement (i.e., they either were or were not an alcohol user). However, the question asks if they’ve had one drink in the last 12 months. If this is the case, it seems as though this question is missing out on quite a bit of variation in use of alcohol. I’m also not sure if it would be appropriate to classify someone who had one drink nearly a year ago as an alcohol user.

• In the results, the author does not mention the fact that correlations between measures of SC and MMSE are small. Social cohesion has a correlation of .12, while social interaction has a correlation of .009. While these may be significant, they are quite small. Recognition of this fact might be appropriate to discuss in the results and discussion sections.

• Based on Table 3, it looks like social cohesion is not associated with MMSE under model 1, but that it is under model 2. However, in the text, the authors say that social cohesion is associated with MMSE for model 1, and that this association remains after controlling for covariates under model 2. Any results given in-text and in tables/diagrams should match.

• Further, because social capital was measured in two ways (i.e., social cohesion and social interaction), results for these two measures might be easier to understand if they are separated in the text. Perhaps focusing on the analysis for cohesion first and then interaction under separate headings would allow the reader to understand the results for both of these measures more easily.

**********

6. 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: Yes: Vahid Hajali

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 May 27;16(5):e0252208. doi: 10.1371/journal.pone.0252208.r002

Author response to Decision Letter 0

13 Jan 2021

Editor comments

1. In agreement with suggestions of Reviewer 2 I feel that the analysis, and possibly the message, of the paper should undergo a really major revision, as present conclusions seem to have limited support from data.

Response: We have modified the manuscript entirely according to reviewer’s suggestion; now we believe it better than the previous version.

2. In fact the main message of the paper is that social capital is associated with the risk of cognitive decline. Yet correlations between measures of SC and MMSE are small. Social cohesion has a correlation of .12, while social interaction has a correlation of 0.09. Moreover, based on Table 3, it looks like social cohesion is not associated with MMSE in univariate analysis.

Response: Because the research on social capital is biased towards sociology, there are many potential influencing factors, and the effect size is small (usually the effect value of social science is small, but it does not affect the existence of the effect), and this study mainly to explore the mediation effect. In the multivariate analysis, there is a weak correlation between social capital and cognitive decline. The path analysis shows that sleep duration played a mediator role in the relationship between social capital and cognitive decline.

3. The whole hypothesis of the mediation is made uncertain by the cross-sectional design. In fact both low social capital and longer sleep duration might be consequence, rather than predictors, of cognitive decline. In fact the present message of the paper would be that older subjects should sleep less to maintain their social capital, that seems at odds with evidence suggesting an association between shorter sleep time and increased risk of cognitive decline.

Response: We have discussed our findings more comprehensively; now, it’s easier for the reader to understand the relationship between social capital, sleep duration, and cognitive decline. In this study, we mainly focus on the mediation effect of sleep duration, and the results showed social capital was positively associated with cognitive function and negatively associated with sleep duration; meanwhile, sleep duration was also negatively associated with cognitive function, so long sleep duration might be a risk factor for cognitive function. Furthermore, a longitudinal cohort study [1] reported possessing a rich social capital has been associated with better cognitive function among the old adults. Robbins et al. found lower social capital members in groups were seen for long sleepers [2]. Additionally, as described in a review [3], sleep fragmentation can result in poor quality sleep, depression, and underlying disease processes, such as CHD, which appear to be relevant to the association between long sleep and cognitive function. Reverse causality, the possibility that cognitive function determines sleep duration, cannot be ruled out in our analyses. However, the longitudinal data [4] revealed that sleep duration “increase from 7 or 8 hours” was associated with lower cognitive function scores. Meanwhile, a previous study [5] has also provided no firm evidence that cognitive decline predicts sleep duration.

[1]. Bennett DA, Schneider JA, Tang Y, Arnold SE, Wilson RS. The effect of social networks on the relation between Alzheimer's disease pathology and level of cognitive function in old people: a longitudinal cohort study. Lancet Neurol. 2006; 5(5): 406-412.

[2] Robbins R , Jean-Louis G , Gallagher R A , et al. Examining Social Capital in Relation to Sleep Duration, Insomnia, and Daytime Sleepiness[J]. Sleep Medicine, 2019.

[3] Grandner MA, Drummond SP. Who are the long sleepers? Towards an understanding of the mortality relationship. Sleep Med Rev 2007;11:341-60.

[4] Ferrie J E , Shipley M J , Akbaraly T N , et al. Change in sleep duration and cognitive function: findings from the Whitehall II Study.[J]. Sleep(5):565-73.

[5] Yaffe K, Blackwell T, Barnes DE, Ancoli-Israel S, Stone KL. Preclinical cognitive decline and subsequent sleep disturbance in older women. Neurology 2007;69:237-42.

4. As further statistical suggestion, MMSE distribution is probably non-normal. It would be probably better to categorize it and perform a multinomial regression instead of a linear regression analysis. It would be of interest to include in the same model as predictors social capital, sleep time and interaction between the two factors.

Response: Yes, as you mentioned, the MMSE score fit a non-normal distribution. Thus, we performed a logarithmic transformation of the MMSE score to finish the mediation effect modeling that requires continuous data, and linear regression employed in the univariate analysis consequently. Besides, categorizing continuous variables may lose much information of the original variable and severely downward precision of the effect estimation.

Reviewer #1

1. Introduction: Overlay, this section has been prepared orderly. In the last paragraph, authors want to point the relationship between sleep duration and cognitive functions and properly reference to the study which conclude that homocysteine and beta amyloid may mediate the effects of poor sleep on cognition. However, ref 22 (smoking and sleep) here is not related to the main issue and I think it should be removed and instead another relevant ref can be added.

Response: Now, we have removed the description of “previous study revealed that sleep duration plays a significant mediating role in the relationship between smoking and mild cognitive impairment [22]” in the last paragraph of introduction and ref 22 (smoking and sleep).

2. Line 133: the fifth domain of MMSE is vague. Please refine it.

Response: We has refined the fifth domain of MMSE as constructional praxis (coping task, eg. copying intersecting pentagons), can be seen in line 132 -133.

3. Sleep duration: I am wondering why the authors did not consider the sleep quality rather than sleep duration. Then, they could easily use the well-known and standard scale, Pittsburgh sleep questionnaire

Response: The relationship between sleep quality and health has been well studied in the past decades; We believe sleep duration is one dimension of sleep quality, at least among old adults. And more and more research has focused on the relationship between sleep duration and cognitive function; to our knowledge, no study was conducted among Chinses old adults who were living in different cultural backgrounds from other countries.

4. Discussion: in the second paragraph which deals with the association between sleep duration and cognition, authors remark the sleep fragmentation and OSA as the possible causations of long sleep duration and low MMSE scales. But, I can’t understand why the authors mention here to the short sleep duration as this is a very definite and old finding and also they have no data on this issue. Rather, more relevant findings regarding the physiological alteration associated with long sleep duration could be of most benefits.

Response: We removed the description of short sleep duration. And there another possible explanation: “Besides, long sleep duration has been associated with an increased level of inflammatory factors and elevated inflammatory cytokine levels increase the risk of cognitive decline” in line 240.

5. Discussion: the last paragraph regarding the positive correlation of SC and MMSE scores could be discussed more deeply with mentioning to the some relevant basic findings.

Response: We have extensively edited the discussion section to explain the relationship between SC and cognitive function. See “Furthermore, a recent study manifested that social capital could help older adults continue to independently live in local communities and handle life stressors efficiently, even when they encounter declines in their physical and cognitive health. Additionally, social capital can provide older residents with a sense of security and belonging and is an important reserve domain in old age [54].”

6. The whole manuscript should be proof read for some grammatical and spelling errors. The example is in Line 210: there no!

Response: We have checked the grammatical and spelling errors entirely by our colleague at Duke University. All the changes are marked in red.

Reviewer #2

1. There are several issues with the overall writing style and appropriate use of grammar. This issue extends throughout the article.

Response: We have checked the grammatical and spelling errors entirely by our colleague at Duke University. All the changes are marked in red.

2. On line 125, “MMSE” is used for the first time in the text of the article, though the acronym is not explained until the following paragraph. Acronyms should be spelled out upon their first use. This made understanding line 125 a bit difficult.

Response: Many thanks for your suggestions. We have spelled out the acronym of MMSE in the last third line of the field process part and marked in red.

3. Further, the explanation of how the MMSE is scored in the Method section is a bit tricky to decipher. It is unclear if lower scores translate to cognitive impairment, or if higher scores do. This will help with understanding the beginning of the discussion section where the results are summarized.

Response: We have clarified this concern in line 132 in the Methods section; the higher MMSE score reflects the lower cognitive decline levels.

4. On line 194, no r values are given for the association between social cohesion/interaction and MMSE. Only one p-value is provided here.

Response: We have added r values and p-value for the association between social cohesion/interaction and MMSE. See line 195 “both the social cohesion (r=0.12, P<0.001) and social interaction (r=0.09, P<0.05) was positively correlated with MMSE score”.

5. On line 221, the author states “SC leads to better cognitive performance…” However, this study cannot provide any causal interpretations of the data since there was no manipulation of variables.

Response: We have rewritten the sentence as “the positive relationship between SC and better cognitive performance in older Chinese adults was found”, can be seen in line 224-225.

6. On line 222, the author states that SC is negatively associated with risk of cognitive decline, but the correlations between social cohesion/interaction and MMSE were positive. Further, on line 251, the author then states that SC is positively correlated with MMSE. These statements should be edited so that they agree with the data.

Response: As we noted in line 132, a higher MMSE score reflects the lower cognitive decline levels. So SC is positively correlated with MMSE means, which is negatively associated with the risk of cognitive decline.

7. In the results, it was unclear why analyses were done both with those who slept less than 8 hours and those who slept 8 hours +. Perhaps a brief discussion of this in the methods or in the results section would help the reader better understand this analysis.

Response: The average sleep duration of the total participants was 8.1 hours, and we categorized the sleep duration into two groups using a cutoff point of 8 hours. We revised this as “Considering the U-shape relationship between sleep duration and cognitive decline, the exploring analysis conducted stratified (as a cutoff point of mean sleep duration of the total population) by sleep duration showed in Table 5”.

8. The paragraph starting on line 226 seems to be making the point that there is evidence that both long and short sleep are connected to cognitive decline. However, the language pointing to this conclusion seems to be a little vague in this paragraph. Specifically, there is a sudden jump from talking about evidence about longer sleep duration to shorter sleep duration. A transition word or sentence might help to bridge this gap and clarify the overall point of this paragraph.

Response: Same with the editor’s comments 3, now, we have removed the description of short sleep duration.

9. The paragraph starting on line 242 seems to have a similar issue. The point here appears to be that people with more social capital are busier, and thus are getting less sleep, but this point again seems to be vague and somewhat difficult for the reader to decipher.

Response: Due to the U-shape relationship between sleep duration and cognitive function, here our findings support that people with high social activities may keep them in appropriate sleep duration, that means not too short neither too long. Another possible explanation as you mentioned that keep busy may helpful for older adults stay in bed unexpected long time.

10. The measurement of sleep duration appears to be problematic. Specifically, I’m not sure how appropriate it is to simply add 1 hour to the overall calculated sleep duration if someone answers “yes” to the question about whether they napped. Ideally, a follow-up question could have asked respondents who indicated napping how long they were asleep during the nap. This kind of information is fairly easy to record, so it is unclear why that was not originally built into the design.

Response: We have mentioned in the limitation part as “bedtime and sleep duration were collected via a self-reported survey question; it may involve information bias despite it be commonly used in the epidemiological study due to the feasibility consideration”. In addition, the previous research [1] reported a good correlation when comparing the measurement (subjective and actigraphic measurement) of sleep timing and duration. Furthermore, here the bedtime we asked was the actual sleep onset time, and considering the local life culture, people may like an afternoon nap; we also ask the question ‘Do you sleep at the afternoon?’.

55. Lockley S W, Skene D J, Arendt J. Comparison between subjective and actigraphic measurement of sleep and sleep rhythms. Journal of Sleep Research. 1999; 8:175-183.

11. The measurement of alcohol use seems a bit unclear. Based on the article, it appears that this might have been a yes/no measurement (i.e., they either were or were not an alcohol user). However, the question asks if they’ve had one drink in the last 12 months. If this is the case, it seems as though this question is missing out on quite a bit of variation in use of alcohol. I’m also not sure if it would be appropriate to classify someone who had one drink nearly a year ago as an alcohol user.

Response: Yes, we have defined the alcohol use as: a drink at least one glass of alcohol (that equal to 1/2 bottle of beer or 125-milliliter grape wine or fruit wine or 40-milliliter white wine) in the past 12 months, seen in line 165-167. In our study, alcohol users include someone who had one drink a year ago, and in the past year.

12. In the results, the author does not mention the fact that correlations between measures of SC and MMSE are small. Social cohesion has a correlation of .12, while social interaction has a correlation of .009. While these may be significant, they are quite small. Recognition of this fact might be appropriate to discuss in the results and discussion sections.

Response: Because the research on social capital is biased towards sociology, there are many potential influencing factors, and the effect size is small (usually the effect value of social science is small, but it does not affect the existence of the effect), and this study mainly explores the mediation effect. In the multivariate analysis, there is a weak correlation between social capital and cognition. The analysis shows that sleep duration is the mediation variable. The interpretability of the analysis results is explained from the perspective of path analysis. We supplemented the description in line 196-197 of results and marked in red.

13. Based on Table 3, it looks like social cohesion is not associated with MMSE under model 1, but that it is under model 2. However, in the text, the authors say that social cohesion is associated with MMSE for model 1, and that this association remains after controlling for covariates under model 2. Any results given in-text and in tables/diagrams should match.

Response: We have revised the description of the tables, and now the results given in text matched the tables.

14. Further, because social capital was measured in two ways (i.e., social cohesion and social interaction), results for these two measures might be easier to understand if they are separated in the text. Perhaps focusing on the analysis for cohesion first and then interaction under separate headings would allow the reader to understand the results for both of these measures more easily.

Response: We have clarified this as: Social capital is measured with one instrument with two dimensions, social cohesion and social interaction, not two ways, so we analyzed together in our study.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (32.1KB, docx)

Decision Letter 1

Enrico Mossello

18 Feb 2021

PONE-D-20-28198R1

Social capital and cognitive decline: does sleep duration mediate the association?

PLOS ONE

Dear Dr. Wang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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

ACADEMIC EDITOR:

I have appreciated the way Authors have refocuesed the discussion. However I would advise to be more cautious whan (in the Abstract) thay state that "improvement of sleep duration may help in maintaining cognitive function", as literally this would be to make people sleep less, which is clearly not the message of the data.

Moreover, I have asked for a statistical revision of the manuscript, as I was not sure of the methodological robustness of findings, due to the small association observed between social cohesion and cognitive function (even non significant in Regression model 1, Table 3), thus making the whole assumptions of a mediation analysis uncertain.

Comments of the reviewer are quite reassuring. Yet I feel that the question regarding how you adjusted the variables in the regression analysis is important (which in the form of quantitative, dichotomous, and categorical), to be sure that the assumptions of the regression model are fulfilled. Moreover, the analyses were adjusted with many variables which could lead to multicollinearity issue.

The reviewer also suggests to use Structural Equation Modelling (SEM) approach to give a clearer picture of the overall pathway direction involving the variables and to validate the findings.

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

Please submit your revised manuscript by 3-APR-2021. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Enrico Mossello

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

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 #3: (No Response)

**********

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: Partly

**********

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

Reviewer #3: No

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: The manuscript entitled ‘Social capital and cognitive decline: does sleep duration mediate the association?’ with the aim to examine the mediation effect of sleep duration on the relationship between social capital and cognitive decline in Chinese older adults.

This is quite an interesting study; however, the manuscript requires further improvement.

Comments

Page 8 Line 156-157, adding an hour to the sleep count for someone who took afternoon nap is less accurate without asking the subjects the number of hours.

Page 9 Line 169-170, proper citation for SPSS including publisher name to be stated.

Page 9 Line 165, the definition criteria for alcohol use is inaccurate and could have classified it in a day or in a week for the past 12 months.

Page 9 Line 173, the sentence requires revision.

Page 9 Line 177, for Hayes [28]was, was to be spaced out.

Results

Page 10 Table 1, proper symbol for chi-square to be provided. The symbol chi-square and t and statistical tests which were employed in Table 1 to be stated in the statistical analysis section and denoted in the table footnote.

Page 11 Table 2, an explanation or a note to be provided on how the variables other than continuous/dichotomous variables were adjusted in the partial correlation in the table footnote. The name of correlation coefficient to be stated.

Page 11 Line 197, r=-0.09 to be replaced with r=-0.11

Page 11 Line 200, what ‘multivariate’ refers to in Table 3 to be clearly denoted.

Page 12 Table 3, Model 2 and Model 3 in the table footnote to be written in a new line. Symbol β to be denoted in the table footnote. There were many variables with different type of data/scale of measurement other than continuous/dichotomous variables that were adjusted in the analysis. How these variables were coded and employed in the analysis to be clearly stated (Likewise with Table 4). A note on statistical assumptions fulfillment would be useful. Model summary to be provided.

Page 13 Line 216-219, Table 5, whether the analysis were adjusted or otherwise to be clearly stated.

SEM approach could be explored or as a validation for the regression analysis.

Not all references conformed to the journal format.

**********

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

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 May 27;16(5):e0252208. doi: 10.1371/journal.pone.0252208.r004

Author response to Decision Letter 1

8 Mar 2021

ACADEMIC EDITOR:

1. I have appreciated the way the Authors have refocuesed the discussion. However I would advise to be more cautious whan (in the Abstract) thay state that "improvement of sleep duration may help in maintaining cognitive function", as literally this would be to make people sleep less, which is clearly not the message of the data.

Response: We have rephrased the conclusion as " It may be a suggestive clue to identify those at a higher risk of progressing to cognitive impairment.”

2. Moreover, I have asked for a statistical revision of the manuscript, as I was not sure of the methodological robustness of findings, due to the small association observed between social cohesion and cognitive function (even non significant in Regression model 1, Table 3), thus making the whole assumptions of a mediation analysis uncertain.

Response: Our results found a significant association between social cohesion and cognitive function after adjust the potential covriates (β=0.16, P=0.005) with a effect size (R square) 0.393 (this is a large effect size) , considering the precedently increased number of older adults world widely, and the few chanagable predictors available to reduce the cognitive disorders, our findings provide primary evidence that support comprehensive interventional program in need to maintain the cognitive function in community level and individual level.

Also, we have performed sensitivity analysis using the SEM, and the results validated the methodological robustness of mediation analysis (Fig 3). And there are statisticians suggested that the significant association of dependent variable with independent variable is unnecessary in the process of mediation analysis (Zhao et al, 2010).

Zhao X , Jr J G L , Chen Q . Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis[J]. Journal of Consumer Research, 2010, 37(2):197-206.

3. Comments of the reviewer are quite reassuring. Yet I feel that the question regarding how you adjusted the variables in the regression analysis is important (which in the form of quantitative, dichotomous, and categorical), to be sure that the assumptions of the regression model are fulfilled. Moreover, the analyses were adjusted with many variables which could lead to multicollinearity issue.

Response: In this study, we used the quantitative form of the variable. All descriptions can be seed in line158-169 of pages 8-9. Meanwhile, we conducted the collinearity diagnostics, and the results revealed no multicollinearity among those variables. As shown below, where the tolerance >0.1 and Variance Inflation Factor (VIF) <5 indicate multicollinearity can be ignored (Mason, 1991).

The collinearity diagnostics

　 tolerance VIF tolerance VIF

age 0.927 1.078 BMI 0.975 1.026

gender 0.640 1.562 smoking 0.705 1.419

residence 0.702 1.424 alcohol use 0.793 1.262

marital status 0.936 1.069 FPG 0.987 1.013

education 0.619 1.615 hyperlipidemia 0.973 1.028

ethnicity 0.808 1.237 hypertension 0.953 1.050

family income 0.645 1.551

Dependent variable: MMSE score

4. The reviewer also suggests to use Structural Equation Modelling (SEM) approach to give a clearer picture of the overall pathway direction involving the variables and to validate the findings.

Response: We have performed the SEM analysis. The results as shown in Fig 3. The findings are consistent with the Bootstrap methods of PROCESS.

Fig 3 The path analysis of the mediation effect of sleep duration in the relationship between social cohesion and MMSE

Reviewers' comments:

1. Page 8 Line 156-157, adding an hour to the sleep count for someone who took afternoon nap is less accurate without asking the subjects the number of hours.

Response: As any self-report measurement, the accuracy of data can not fully be guaranteed. According to our study, most people reported that their afternoon nap time was more or less 1 hour; statistically, it’s reasonable to adjust the total sleep hour by adding one hour to those who report having an afternoon nap.

2. Page 9 Line 169-170, proper citation for SPSS including publisher name to be stated.

Response: We revised the description of SPSS as “Analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 24.0 (IBM Inc., Chicago, Illinois, USA)”.

3. Page 9 Line 165, the definition criteria for alcohol use is inaccurate and could have classified it in a day or in a week for the past 12 months.

Response: We have modified the definition as: a drink of at least one glass of alcohol, that equals 1/2 bottle of beer or 125-milliliter grape wine or fruit wine or 40-milliliter white wine, in a day for the past 12 months.

4. Page 9 Line 173, the sentence requires revision.

Response: We revised the sentence “A correlation matrix was created using partial correlations under controlling for age, gender, ethnicity, residence, educational attainment, marital status, family income, BMI, smoking, alcohol use, FBG, hyperlipidemia, hypertension” as “Partial correlations were employed to create correlation matrix under controlling for age, gender, ethnicity, residence, educational attainment, marital status, family income, BMI, smoking, alcohol use, FBG, hyperlipidemia, hypertension”.

5. Page 9 Line 177, for Hayes [28]was, was to be spaced out.

Response: we rephrased the sentence as “Bootstrap methods of PROCESS developed by Hayes was employed to test the mediation effect of sleep duration on the relationship between SC and MMSE score [29]”.

6. Page 10 Table 1, proper symbol for chi-square to be provided. The symbol chi-square and t and statistical tests which were employed in Table 1 to be stated in the statistical analysis section and denoted in the table footnote.

Response: We have symbolled the two different tests in table 1 and denoted the symbol of chi-square and t-tests in the Table 1 footnote.

7. Page 11 Table 2, an explanation or a note to be provided on how the variables other than continuous/dichotomous variables were adjusted in the partial correlation in the table footnote. The name of the correlation coefficient to be stated.

Response: We have added a footnote as “The covariates include age, gender, ethnicity, residence, education, marital status, family income, BMI, smoking, alcohol use, FBG, hyperlipidemia, hypertension were adjusted using Partial correlation method.”

8. Page 11 Line 197, r=-0.09 to be replaced with r=-0.11

Response: We have corrected this error.

9. Page 11 Line 200, what ‘multivariate’ refers to in Table 3 to be clearly denoted.

Response: We have clarified this issue, and denoted in the Table 3 where explained each of the models.

10. Page 12 Table 3, Model 2 and Model 3 in the table footnote to be written in a new line. Symbol β to be denoted in the table footnote. There were many variables with different type of data/scale of measurement other than continuous/dichotomous variables that were adjusted in the analysis. How these variables were coded and employed in the analysis to be clearly stated (Likewise with Table 4). A note on statistical assumptions fulfillment would be useful. Model summary to be provided.

Response: in Table 3, Model 2 and Model 3 in the table footnote have already been written in a new line and Symbol β was denoted in the table footnote. Additionally, variables other than continuous/dichotomous variables that were marital status and family income, we coded them in page 16 of measurement section. Model summary was provided in Statistical Analyses section as well as denoted in the table 3.

Three separate linear regression models were performed to examine the association among SC, sleep duration, and MMSE. In summary, model l include the SC and sleep duration; model 2 adjusted with covariate variables (age, gender, ethnicity, residence, education, marital status, family income, body mass index, smoking, alcohol use, fasting blood glucose, hyperlipidemia, hypertension); and the interaction between SC and sleep duration were added in model 3. Social interaction and social cohesion were tested separately in all the models.

11. Page 13 Line 216-219, Table 5, whether the analysis were adjusted or otherwise to be clearly stated.

Response: Yes, the analysis were adjusted covariate variables, and we supplemented the description “After controlling for age, gender, ethnicity, residence, education, marital status, family income, BMI, smoking, alcohol use, FBG, hyperlipidemia, hypertension.” In the table 5 footnote.

12. SEM approach could be explored or as a validation for the regression analysis.

Response: We peformed the SEM approach to validate the findings, can be seen in sensitivity analysis section and the results showed in Fig 3.

13. Not all references conformed to the journal format.

Response: We have formatted the reference list carefully; now it’s more suitable for the journal style.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (62.2KB, docx)

Decision Letter 2

Y Zhan

29 Apr 2021

PONE-D-20-28198R2

Social capital and cognitive decline: does sleep duration mediate the association?

PLOS ONE

Dear Dr. wang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jun 13 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Y Zhan

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

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 #3: (No Response)

**********

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: Partly

**********

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

Reviewer #3: (No Response)

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: Yes

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: The authors have put in great effort to address the comments.

Minor clarification/revision required.

Line 160, for marital status (unmarried, married and widowed/divorced), was the variable collapsed (0.1) for the regression analysis?

Line 161- 161, it was mentioned that family income <1,000 RMB,162 1,000-1,999 RMB, 2,000-2,999 RMB, 3,000-4,999 RMB, and 5,000 RMB or more were collected. For Table 1, was the family income variable coded as <1000 and ≥ 1000 (0 and 1)? If so, which one was used in the regression analysis; (0.1) or scale data?

Line 200, likewise for the partial correlation analysis, marital status and family income to be clearly denoted.

Education to be revised to Educational attainment (years).

**********

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

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 May 27;16(5):e0252208. doi: 10.1371/journal.pone.0252208.r006

Author response to Decision Letter 2

1 May 2021

Dear editor:

We are submitting the revised manuscript titled “Social capital and cognitive decline: does sleep duration mediate the association?” for publication. We have modified the manuscript along the lines suggested by editors and reviewers. In addition, we re-checked the reference and now it is complete and correct. All the changes are marked in red.

Below are our responses to the reviewer’s comments point by point.

1. Line 160, for marital status (unmarried, married and widowed/divorced), was the variable collapsed (0.1) for the regression analysis?

Response: We devided marital status into two categories (married vs. unmarried/widowed/divorced) in all the statistical analysis due to the few reponders are unmarried (10 of the 955). And we have running the analysis procedure again, all the changes marked in red.

2. Line 161- 161, it was mentioned that family income <1,000 RMB,162 1,000-1,999 RMB, 2,000-2,999 RMB, 3,000-4,999 RMB, and 5,000 RMB or more were collected. For Table 1, was the family income variable coded as <1000 and ≥ 1000 (0 and 1)? If so, which one was used in the regression analysis; (0.1) or scale data?

Response: The value of family income was ordinal variable in the regression model (divided into five degree: <1,000 RMB,162 1,000-1,999 RMB, 2,000-2,999 RMB, 3,000-4,999 RMB, and 5,000 RMB or more). We have also rehearched it in statistical analysis part as “family income (ordinal)”, marked in red.

3. Line 200, likewise for the partial correlation analysis, marital status and family income to be clearly denoted.

Response: As described above, We have revised the marital status and family income as marital status (married vs. not married (included unmarried and widowed/divorced)), family income (ordinal)”, now it is more clearly.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (18.2KB, docx)

Decision Letter 3

Y Zhan

12 May 2021

Social capital and cognitive decline: does sleep duration mediate the association?

PONE-D-20-28198R3

Dear Dr. wang,

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

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,

Y Zhan

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Y Zhan

18 May 2021

PONE-D-20-28198R3

Social capital and cognitive decline: does sleep duration mediate the association?

Dear Dr. Wang:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. 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.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Y Zhan

Academic Editor

PLOS ONE

Associated Data

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

    Supplementary Materials

    S1 Data

    (SAV)

    Click here for additional data file. (123.6KB, sav)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (32.1KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (62.2KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (18.2KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its Supporting Information files.

    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES