Quality of life and cognitive assessment in healthy older Asian people with early and moderate chronic kidney disease: The NAHSIT 2013-2016 and validation study.

BACKGROUND: Taiwan has the highest prevalence of chronic kidney disease (CKD). Impaired cognition and quality of life are significant phenomena in the late stages of CKD. We sought to obtain an overview and the attributable effect of impaired glomerular filtration on multiple domains in cognition and dimensions of quality of life for community-based healthy older adults in Taiwan.
METHODS: The study was derived from the Nutrition and Health Survey in Taiwan (NAHSIT) 2013-2016, a nationwide cross-sectional study conducted to sample healthy, community-based older adults aged ≥65 years in Taiwan. Participants were categorized into four CKD groups: CKD stage 1, stage 2, stages 3a and 3b, and stages 4-5. The Mini-Mental State Examination (MMSE) and the QoL questionnaire derived from the 12-item Short Form Health Survey (SF-12) were measured. Generalized linear mixed models (GLMMs) and principal component regressions were employed for the analysis and validation, respectively.
RESULTS: Participants with moderate CKD (stages 3a and 3b) showed deficits in global MMSE, domain orientation to time, calculation, complex commands, and role-physical and vitality in QoL questionnaires. In GLMMs, impaired eGFR per 30 mL/min/1.73 m² was associated with lower global MMSE scores (β = -0.807, standard error [SE] = 0.235, P = 0.0007), domain orientation to time (β = -0.155, SE = 0.047, P = 0.0011), calculation (β = -0.338, SE = 0.109, P = 0.0020), complex commands (β = -0.156, SE = 0.079, P = 0.0494), and role-physical (β = -2.219, SE = 0.779, P = 0.0046) dimensions of QoL.
CONCLUSIONS: Elderly Han Chinese adults with moderately impaired renal filtration could manifest cognitive deficits in orientation to time, calculation, and impaired quality of life in physical role functioning.

Introduction

High prevalence of chronic kidney disease in Taiwan

In Taiwan, the incidence rate and prevalence throughout all stages of kidney disease were approximately 27,210 per million person-years and 154,600 per million people in the last decade [1]. According to the United States Renal Data System (USRDS) annual report in 2020 [2], Taiwan has the highest prevalence of end-stage renal disease (ESRD) (3,587 per million population) and the highest prevalence of dialysis (3,429 per million population) worldwide [3, 4]. In addition, the USRDS in 2020 [2] reported that the prevalence of ESRD is highest in the age group of 45–64 years (25,156 per million population), compared to 20–44 years (5,290 per million population), 65–74 years (17,194 per million population), ≥75 years (15,066 per million population). Due to improved management for CKD patients, life expectancy [5, 6] and social burden of care [7] are both expected to increase in Taiwan.

Measures of chronic kidney disease

Renal disease is assessed by the degree of injured kidney filtration rate [8, 9], and CKD is relatively asymptomatic until the end stage [10]. The most commonly used measure is estimated glomerular filtration rate (eGFR) by serum creatinine, which evaluates the degree to which the kidneys remove waste from the blood. According to eGFR, CKD is divided into six categories by the international guideline group Kidney Disease Improving Global Outcomes (KDIGO) [11]: early CKD of stage 1 (eGFR of > 90 mL/min/1.73 m2), stage 2 (eGFR of 60–89 mL/min/1.73 m2), stages 3a (eGFR of 45–59 mL/min/1.73 m2), and 3b (eGFR of 30–44 mL/min/1.73 m2), late CKD stage 4 (eGFR of 15–29 mL/min/1.73 m2), and stage 5 ESRD (eGFR < 15 mL/min/1.73 m2). In addition, eGFR is modified by age, sex, and ethnic group [12-14].

Cognitive impairment in chronic kidney disease

Theoretically, the brain and kidney have similar microvascular structures and are susceptible to hemodynamic fluctuations [15-17]. Recent studies suggested that cognitive impairment is associated with cardiovascular risk factors, such as hypertension, hyperlipidemia [18, 19], and diabetes mellitus [20, 21]. Similar to the brain, the kidney receives a large amount of blood flow: 1.0–1.2 liters per minute per 1.73 m2 of body surface area, approximately 20–25% of the total cardiac output [22]. When renal function deteriorates, uremic toxins and waste from blood are not removed, and the build-up of toxins impairs brain function [23]. A recent study [24] showed that CKD mainly affects the cortical synchronization of neurons in electroencephalography. Dementia is recognized as a significantly common phenomenon in ESRD, affecting as high as 40% of patients [25]. Studies have reported that ESRD patients treated with hemodialysis exhibited cognitive impairment in the domains of orientation, attention, memory, construction, and executive function [26, 27]. Additionally, ESRD patients who received kidney transplant showed a higher incidence of dementia [28]. While the vast majority of studies which investigated patients with both renal function injury and cognitive function focused on late CKD and ESRD populations, to date, few studies have evaluated cognitive impairment in early CKD stages [29].

Mild cognitive impairment (MCI), an intermediate cognitive state between normal and full-blown dementia, is characterized by problems with orientation, attention, judgment, and memory [30, 31], and has been reported to be associated with cardiovascular risk factors in the last two decades. Recently, there have been increasing studies supporting the association between CKD and MCI. Two recent meta-analyses [32, 33] showed that impaired eGFR is associated with cognitive impairment and can be present in the early and late stages of CKD. A systematic review [29] included three relevant studies on CKD patients <65-years-old, which found that these patients had slow processing speed [34], impaired verbal learning [35, 36], and impaired working memory [35] in moderate stages of CKD. A survey of Japanese CKD patients [37] demonstrated that female participants with eGFR <90 mL/min/1.73 m2 showed a faster rate of cognitive decline than those with eGFR ≥90 mL/min/1.73 m2.

Quality of life in chronic kidney disease

The term “quality of life” can be traced back to the definition in 1948 by the World Health Organization (WHO) as a state of perception of “physical, mental, and social well-being, and not merely the absence of disease” [38]. Prior meta-analysis [39] assessed the utility-based quality of life with the 12-item or 36-item Short Form Health Survey (SF-12 or SF-36), EuroQol Group’s EQ-5D, and other instruments, which suggested that dialysis is significantly associated with reduced quality of life for ESRD patients. However, few studies have investigated the association between quality of life and the early and moderate stages of CKD. We found that these studies exhibited inconsistent results: (1) a cross-sectional study of ≥60 year-old participants in North California [40] showed no relationship between eGFR and quality of life scores in physical and mental dimensions after adjustment for medical comorbidities; (2) a cross-sectional study including ≥50 year-old Irish participants [41] showed that reduced scores in quality of life are associated with eGFR by serum cystatin rather than creatinine; and (3) a recent cross-sectional study [42] enrolled 2,255 older adults in European countries and found that early CKD at stages 3a and 3b, defined by the BIS equation, is associated with lower quality of life on the EQ-Visual Analogue Scale (EQ-VAS). To our knowledge, there is a lack of relevant research on ethnic Han Chinese as well.

Study rationale and aims

Cognitive impairment or dementia is associated with increased physical disability [43, 44] and worsened caregiver burden [45]. While The World Health Organization (WHO) defined a society in which the proportion of people aged ≥65 years is 7% or higher is known as an “aging society,” 14% or higher is regarded as an “aged society,” and the prevalence of older adults in Taiwan exceeded 14% in 2018. Since Taiwan has become an aged society and has the highest worldwide prevalence of CKD and ESRD [2], assessment of cognition in CKD is of paramount importance. In this study, we hypothesized that the high prevalence of cognitive impairment in older adults with CKD in Taiwan, and perception of the physical and mental well-being of older adults was worsened in the early and moderate stages of CKD. In this cross-sectional study, we aimed to (1) obtain an overview of cognitive impairment and quality of life at each stage of CKD in the Han Chinese population, and (2) assess the attributable effect of poor kidney filtration function, after adjusting for demographic factors, on multiple cognitive domains and dimensions of quality of life among community-based healthy older adults in Taiwan. Additionally, we performed a validation study to examine the robustness of the association between eGFR, cognitive impairment, and quality of life. The existence of collinearity in our data analysis was likely since multiple domains of cognition and multiple dimensions of life quality were assessed. We replaced the conventional regression models with partial least squares (PLS) regressions to deal with potential collinearity and confirm robustness.

Methods

Study design and participants

The Nutrition and Health Survey in Taiwan (NAHSIT) 2013–2016 [46] was a nationwide cross-sectional study in Taiwan, which was conducted from January 1, 2013 to December 31, 2016. The primary objective of conducting NAHSIT 2013–2016 by the Health Promotion and Administration, Ministry of Health and Welfare in Taiwan was to determine the nutritional status of the Taiwanese population, which was used as a reference for nutrition and health policymaking in a government entity. The NAHSIT involved a systematic and stratified sampling process that covered all 359 townships and city districts in Taiwan, and was divided into eight strata according to population density and geographical area. The content of the survey included (1) behavioral indicators, such as cognition and quality of life assessment; (2) health outcome indicators, such as cardiovascular disease and kidney disease; and (3) laboratory tests of clinical chemistry, such as serum creatinine, lipid profiles, and blood glucose. Data collection was for the primary objective of the study. All participants were visited once during the study period. Our study was a secondary analysis of data derived from NAHSIT 2013–2016. Data for participants aged ≥65 years who completed the MMSE and QoL questionnaire of the 12-item Short Form Health Survey (SF-12) were collected. Participants who had no laboratory examination of renal function were excluded. This study was approved by the Institutional Review Board of Biomedical Science Research, Academia Sinica, Taiwan (AS-IRB01-13067) and the Research Ethics Committee, National Health Research Institutes, Taiwan (EC1020110). Written informed consent was obtained from all participants.

Cognitive and life quality measures

In Taiwan, the most widely used cognitive assessment tool is the culturally adapted traditional Chinese version of the Mini-Mental State examination (MMSE) [47]. The norms have been validated in the Taiwanese population [48] and other Han Chinese populations [49, 50]. The traditional Chinese version of the MMSE includes questions on orientation to time (5 points), orientation to place (5 points), registration (3 points), calculation (5 points), memory recall (3 points), language (2 points), repetition (1 point), and complex commands (6 points), and the MMSE score ranges from 0 (worst) to 30 (best) [51, 52]. For the Taiwanese population, the norms [48] indicated 2 cutoff scores for determining cognitive impairment: a value of <27 for the literate and another value of <16 for the illiterate, respectively.

The most well-validated tool for assessment of quality of life for the Taiwanese population is the Traditional Chinese version of the SF-36 [53, 54]. Despite being valid and equivalent for Han Chinese and other ethnic groups, SF-36 is limited by its length and time-consuming characteristics. The traditional Chinese version of SF-12, an abbreviated form of SF-36, is validated as equivalent to SF-36 for assessing the dimensions of physical and mental health [55]. The SF-12 questionnaire includes five dimensions of concepts: role-physical (RP), vitality (VT), social functioning (SF), role-emotional (RE), and mental health (MH). Each concept was transformed into a scale ranging from 0 to 100, with a mean distribution of 50 and a standard deviation of 10. A higher score signifies a perception of a better quality of life [56, 57].

Data collection process

Door-to-door visits were conducted by trained interviewers to collect demographic characteristics; culturally adapted traditional Chinese version of the MMSE [48] and SF-12 were administered. After informed consent was obtained from participants, phlebotomy was conducted for laboratory assessments of blood urea, nitrogen, creatinine, blood glucose, HbA1c, and lipid profiles of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. Blood pressure measurements were performed by trained public health nurses and after participants rested for 5 minutes with the arm placed at the same height as the heart. A standard sphygmomanometer with an appropriate cuff size was used. Blood pressure measurements were recorded three times, and a fourth measurement was performed if two of the three BP measurements varied by ≥ 10 mmHg. Diabetes mellitus was defined as fasting glucose ≥126 mg/dl or HbA1c level ≥6.5%, in accordance with the standard of the American Diabetic Association [58]. Hypertension was defined as systolic blood pressure (SBP) ≥140 mmHg or diastolic BP (DBP) ≥90 mmHg according to the American Heart Association standard [59].

Definition of chronic kidney disease groups

A previous study [60] indicated poor agreement between the modification of diet in renal disease (MDRD) and the Cockcroft-Gault equations for assessing CKD in cognitively impaired older adults. In Taiwan, citizens are mono-ethnic, and approximately 97% of the Taiwanese are Han Chinese [61]. For older Chinese adults, two studies [62, 63] concluded that eGFR derived from the Berlin Initiative Study (BIS) equation achieved superior accuracy and lower rates of misclassification of CKD stages compared to the MDRD and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations. Because the enrolled participants were healthy older adults in the NAHSIT 2013–2016, eGFR was obtained by the BIS equation (eGFR = 3736 × creatinine0.87 × Age0.95 × 0.82 [if female]) [64, 65]. All participants were categorized into three CKD groups according to the derived eGFR: CKD stage 1 (group 1; eGFR > 90 mL/min/1.73 m2), stage 2 (group 2; eGFR of 60–89 mL/min/1.73 m2), stages 3a and 3b (group 3; eGFR of 30–59 mL/min/1.73 m2), and stages 4–5 (group 4; eGFR of 0–29 mL/min/1.73 m2). Since our study targeted the healthy older population, the number of late CKD stages 4–5 was expected to be small, and therefore Stages 4 and 5 were grouped into one category. In addition to eGFR, we confirmed the CKD risk group stages by urine albumin-to-creatinine ratio (ACR). Compromised renal function allows albumin to pass into the urine. According to the KDIGO [11], urine ACR <30 mg/g is defined as normal to mildly increased albuminuria, urine ACR of 30–300 mg/g as moderately increased albuminuria, and urine ACR >300 as severely increased albuminuria.

Statistical analysis

Demographic characteristics, eGFR, scores on each domain of MMSE, and SF-12 among the four CKD groups were assessed with one-way analysis of variance for continuous variables and with chi-squared or Fisher’s exact test for categorical variables. The P trend for the four CKD groups was estimated using generalized linear models for continuous variables and the Cochran-Armitage trend test for categorical variables. Generalized linear mixed models (GLMMs), containing both fixed and random effects, were applied for data analyses. Because of the study design, which involved a systemic and stratified sampling from the nationwide population in Taiwan and measurements of multiple related factors, a subject-specific model with a random intercept was used. We described this model in the following matrix formula = + , where denotes the matrix containing a set of measures of all items of the MMSE and SF-12 on the ith older adult participant as dependent variables, denotes the matrix containing a set of intercepts, independent variables of eGFR (per 30 mL/min/1.73 m2), and the covariates, denotes the vector of estimated regression parameters, denotes an intercept random effect associated with the ith older adult participant, which has a normal distribution and is independent and identically distributed (i.i.d.); and denotes random error. The covariates used in the GLMMs were none (model 1), a set of variables with age, sex, and interaction of age and sex (model 2), a set of variables with age, sex, and interaction of age and sex, and education years (model 3), and a set of variables with age, sex, and interaction of age and sex, education years, and the characteristics that were imbalanced (defined as P < 0.05) among the four CKD groups (Model 4). All statistical analyses were performed using SAS software (version 9.4; SAS Institute, Cary, NC, USA). Applying the Bonferroni correction with the formula p ≤ α/m, where α was defined as 0.05, and the number of groups for multiple comparisons was 4. In our analysis, a two-tailed p value < 0.0125 (0.05/4) was considered statistically significant.

Validation study

To verify the association between renal function injury, cognitive impairment, and quality of life, we swapped the factors of eGFR in older adults and measured all items of the MMSE and SF-12 in the regression analysis. Conventionally, all items of the MMSE and SF-12 were employed as dependent variables (or response variables), and eGFR was used as an independent variable (or explanatory variable). Instead, we conducted partial least squares (PLS) regressions with the following formula: = + , where denotes the response matrix of eGFR, denotes the factor matrix of all items of the MMSE and SF-12, denotes the matrix of factor loadings, denotes error terms. Spearman’s rank correlation tests were used to examine the correlations among all items of the MMSE and SF-12. One major advantage of PLS regression is that it can easily manage the multicollinearity problem in conditions when there are numerous highly correlated explanatory variables [66, 67]. PLS regressions can help identify the optimal linear combinations of explanatory variables by projecting them to new spaces. The PLS regression was performed using the PROC PLS procedure implemented in SAS 9.4 software, with a factor number of 2 and principal components regression (PCR) to obtain factor loadings. Variables with a factor loading of > |0.3| were considered significant [68].

Results

Participant characteristics

A total of 497 participants were enrolled in this study. Their mean age was 72.2 ± 6.2 years, 213 (42.9%) were female, and the mean score of global MMSE was 26.8 ± 3.4. The prevalence of MCI was 12.7%. The demographic characteristics and laboratory test results of the four CKD groups are shown in Table 1. Of the included participants, 66 (13.3%) had CKD stage 1, 303 (61.0%) had CKD stage 2, 119 (23.9%) had CKD stages 3a and 3b, and 9 (1.8%) had CKD stages 4–5. In groups 1, 2, 3 and 4, the average age evaluations were 68.5 ± 3.8, 71.1 ± 5.2, 76.9 ± 6.6, and 74.3 ± 8.2 years, respectively (P < 0.0001); proportions of female participants were 69.7%, 42.9%, 27.6%, and 44.4%, respectively (P < 0.0001); and eGFR values were 100.3 ± 7.9, 74.2 ± 8.6, 47.7 ± 8.1, and 23.9 ± 4.6 mL/min/1.73 m2, respectively. Regarding sociodemographic characteristics, years of education were lower in groups 3 and 4 (P = 0.0023), and individual income was not significantly different among all CKD groups (P = 0.1435). Medical comorbidities, including hypertension, hyperlipidemia, and diabetes, were not significantly different among the four groups. The systolic and diastolic blood pressures of the four CKD groups were within normal limits, and no significant difference was observed in the mean arterial pressure. In serum laboratory testing, no significant difference was observed in the levels of total cholesterol, LDL-C, triglycerides, and fasting glucose. The levels of HbA1c and HDL-C were not homogenous among the four groups of CKD; however, the mean HbA1c and HDL-C levels were within normal limits.

Table 1

Renal function and mental function health status (N = 497).

CKD Staging	CKD stage 1 (N = 66)	CKD stage 2 (N = 303)	CKD stage 3a, b (N = 119)	CKD stage 4–5 (N = 9)	P value	P trend
Demographic characteristics
Age (years)	68.5 ± 3.8	71.1 ± 5.2	76.9 ± 6.6	74.3 ± 8.2	<0.0001*	<0.0001*
Female Sex (%)	46/ 66 (69.7%)	130/ 303 (42.9%)	33/ 123 (27.6%)	4/ 9 (44.4%)	<0.0001*	<0.0001*
Sociodemographic status
Education years	10.2 ± 4.6	9.1 ± 4.9	7.6 ± 4.8	8.4 ± 3.1	0.0023*	0.0003*
Annual income US$, n (%)	6315.8 ± 4643.4	10484.7 ± 10666.9	8388.2 ± 8973.6	5800.0 ± 4764.5	0.1435	0.5001
Kidney function measures
Blood urea nitrogen	13.8 ± 3.3	15.6 ± 3.7	22.2 ± 6.1	39.0 ± 10.3	<0.0001*	<0.0001*
Creatinine	0.6 ± 0.1	0.8 ± 0.2	1.3 ± 0.3	2.9 ± 1.0	<0.0001*	<0.0001*
eGFR (mL/min/1.73 m2)	100.3 ± 7.9	74.2 ± 8.6	47.8 ± 8.1	23.9 ± 4.6	<0.0001*	<0.0001*
Urine ACR (mg/g)	4.5 ± 18.9	10.8 ± 54.3	34.1 ± 74.2	247.4 ± 325.2	<0.0001*	<0.0001*
Comorbidity
Hypertension (%)	18/ 66 (27.3%)	84/ 303 (27.7%)	44/ 119 (37.0%)	2/ 9 (22.2%)	0.2611	0.1822
Hyperlipidemia (%)	29/ 66 (43.9%)	142/ 303 (46.9%)	45/ 119 (37.8%)	3/ 9 (33.3%)	0.3518	0.1977
Diabetes mellitus (%)	14/ 66 (21.2%)	58/ 303 (19.1%)	37/ 119 (31.1%)	3/ 9 (33.3%)	0.0536	0.0326
Blood pressure
Systolic (mmHg)	135.1 ± 17.9	132.6 ± 18.4	135.5 ± 19.8	133.8 ± 12.8	0.5505	0.6271
Diastolic (mmHg)	76.7 ± 10.0	76.3 ± 10.4	74.8 ± 11.7	73.7 ± 16.5	0.6127	0.2032
MAP (mmHg)	96.2 ± 11.5	95.0 ± 12.0	95.1 ± 13.2	93.7 ± 14.5	0.9296	0.6174
Serum laboratory studies
Fasting glucose (mg/dL)	109.9 ± 34.0	108.5 ± 23.9	113.5 ± 36.9	105.4 ± 19.3	0.4485	0.4189
HbA1c (%)	6.1 ± 1.2	6.1 ± 0.8	6.3 ± 0.9	6.5 ± 0.8	0.0430	0.0224
Total cholesterol (mg/dL)	186.2 ± 34.3	188.2 ± 34.8	180.9 ± 38.4	175.7 ± 32.7	0.2245	0.1198
LDL-C (mg/dL)	116.1 ± 33.3	118.7 ± 31.3	115.6 ± 32.3	117.6 ± 14.5	0.8215	0.7705
HDL-C (mg/dL)	57.2 ± 15.4	53.8 ± 15.3	48.8 ± 14.0	43.7 ± 10.9	0.0003*	<0.0001*
Triglycerides (mg/dL)	115.9 ± 74.6	120.1 ± 71.3	121.5 ± 65.0	105.9 ± 56.2	0.8900	0.8316

Abbreviations: ACR, albumin-to-creatinine ratio; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; MAP, mean arterial pressure; US dollars.

*Statistical significance with Bonferroni correction, P < 0.0125.

Mini-Mental State Examination (MMSE) and life quality assessment

Our assessment of cognitive function with MMSE scores and quality of life for all participants is shown in Table 2. Compared to groups 1 and 2, groups 3 and 4 showed lower scores for each domain of the MMSE. On average, the global MMSE scores for all participants in groups 1, 2, 3, and 4 were 27.4 ± 2.4, 27.4 ± 2.8, 25.3 ± 4.7, and 24.9 ± 3.4, respectively (P < 0.0001 and trend P < 0.0001). The scores for the domains of calculation (P < 0.0001 and trend P < 0.0001), memory recall (P = 0.0018 and trend P = 0.0012), and complex commands (P = 0.0105 and trend P = 0.0047) differed significantly among the four groups. While the scores for the quality of life questionnaire, including dimensions of VT, SF, RE, and MH, did not differ significantly among the four groups, the RP score was significantly impaired in the late stages of CKD. The stratification analysis by sex is shown in S1 Table. Similar to the analysis for all participants, the scores of global MMSE, and the domains of calculation, memory recall, and complex commands were significantly impaired in stages 3a and 3b for both female and male participants. In addition, scores of domains of orientation to place, registration, and memory were significantly impaired in stages 3a and 3b for females.

Table 2

Mini-Mental State examination and quality of life assessment of all participants (N = 497).

CKD Staging	Stage 1 (N = 66)	Stage 2 (N = 303)	Stage 3a, 3b (N = 119)	Stage 4–5 (N = 9)	P value	P trend
Global MMSE (30 points)	27.4 ± 2.4	27.4 ± 2.8	25.3 ± 4.7	24.9 ± 3.4	<0.0001*	<0.0001*
Orientation to time (5 points)	4.9 ± 0.4	4.9 ± 0.5	4.6 ± 0.9	4.3 ± 0.9	<0.0001*	<0.0001*
Orientation to place (5 points)	4.9 ± 0.4	4.9 ± 0.3	4.8 ± 0.7	5.0 ± 0.0	0.1011	0.1627
Registration (3 points)	2.9 ± 0.4	3.0 ± 0.2	2.9 ± 0.4	2.8 ± 0.4	0.1227	0.0883
Calculation (5 points)	4.1 ± 1.3	4.0 ± 1.4	3.3 ± 1.6	2.9 ± 1.7	<0.0001*	<0.0001*
Memory recall (3 points)	2.5 ± 0.9	2.4 ± 0.8	2.1 ± 1.0	2.2 ± 1.0	0.0018*	0.0012*
Language (2 points)	2.0 ± 0.1	2.0 ± 0.1	1.9 ± 0.3	2.0 ± 0.0	0.3403	0.2250
Repetition (1 point)	0.9 ± 0.3	0.9 ± 0.3	0.8 ± 0.4	0.8 ± 0.4	0.2929	0.0900
Complex commands (6 points)	5.3 ± 1.0	5.3 ± 1.1	4.9 ± 1.4	4.9 ± 0.9	0.0105*	0.0047*
Quality of life assessment
Role-physical (RP)	51.2 ± 9.9	50.5 ± 9.6	48.4 ± 10.6	43.0 ± 12.0	0.0288*	0.0074*
Vitality (VT)	51.6 ± 9.8	50.1 ± 9.6	49.1 ± 11.0	46.0 ± 11.1	0.2707	0.0569
Social functioning (SF)	49.3 ± 11.4	50.8 ± 8.7	48.8 ± 11.2	44.1 ± 19.2	0.0664	0.1651
Role-emotional (RE)	49.3 ± 11.0	50.3 ± 9.7	49.5 ± 10.3	48.8 ± 11.4	0.7925	0.8429
Mental health (MH)	50.2 ± 9.4	50.1 ± 10.3	49.5 ± 9.7	50.0 ± 10.5	0.9579	0.6541

CKD, chronic kidney disease; MMSE, Mini-Mental State Examination.

*Statistical significance with Bonferroni correction P < 0.0125.

Association between cognitive impairment and renal function decline with generalized linear mixed models (GLMMs)

The association between impaired eGFR and each dimension of the MMSE and quality of life questionnaire was examined in adjusted GLMMs (Table 3). The relationships among eGFR, age, and sex for global MMSE (Fig 1) and each domain of the MMSE (Fig 2) were plotted. Lowering eGFR per 30 mL/min/1.73 m² was significantly associated with impaired global MMSE score (β = −0.963, standard error [SE] = 0.239, adjusted P < 0.0001), domains of orientation to time (β = −0.161, SE = 0.456, adjusted P = 0.0004), and of calculation (β = −0.397, SE = 0.109, adjusted P = 0.0003). For quality of life assessment, lowering eGFR per 30 mL/min/1.73 m² was associated with impaired scores of RP (β = −2.387, SE = 0.687, adjusted P = 0.0006), but no obvious changes in the dimensions of VT, SF, RE, and MH (Fig 3). The estimated regression parameters β of eGFR in unadjusted and adjusted GLMMs (Models 1–4) are shown in Table 4.

Table 3

Generalized linear mixed model estimates of Mini-Mental State examination and quality of life (adjusted by age and sex).

Scores of each items (N = 497)	eGFR (per 30 mL/min/1.73 m² lower†)			Age (per years increase)			Sex (female versus male)			Age × sex
	β	S.E.	P value	β	S.E.	P value	β	S.E.	P value	β	S.E.	P value
Global MMSE	-0.963	0.239	<0.0001*	-0.067	0.030	0.0280	10.475	3.483	0.0028*	-0.169	0.048	0.0005*
Orientation to time	-0.161	0.456	0.0004*	-0.001	0.001	0.1435	-0.931	0.665	0.1619	-0.015	0.001	0.1086
Orientation to place	-0.014	0.030	0.6299	0.002	0.004	0.6125	1.582	0.437	0.0003*	-0.024	0.006	<0.0001*
Registration	-0.043	0.024	0.0685	0.000	0.002	0.9229	0.338	0.343	0.3242	-0.006	0.005	0.2383
Calculation	-0.397	0.109	0.0003*	-0.029	0.014	0.0346	2.133	1.582	0.1781	-0.036	0.022	0.0964
Memory recall	-0.106	0.063	0.0929	-0.020	0.008	0.0133	1.949	0.918	0.0343	-0.031	0.013	0.0154
Language	-0.007	0.015	0.6566	-0.001	0.002	0.6425	0.205	0.215	0.3419	-0.003	0.003	0.2882
Repetition	-0.030	0.025	0.2317	-0.002	0.003	0.6064	0.179	0.366	0.6252	-0.002	0.005	0.6263
Complex commands	-0.205	0.082	0.0132	-0.001	0.010	0.3897	3.158	1.202	0.0088	-0.051	0.017	0.0022*
Quality of life
Role-physical (RP)	-2.332	0.756	0.0023*	-0.141	0.094	0.1333	-2.976	10.993	0.7867	0.006	0.152	0.9694
Vitality (VT)	-1.815	0.758	0.0170	0.012	0.095	0.9000	6.217	11.095	0.5755	-0.125	0.154	0.4177
Social functioning (SF)	-1.438	0.764	0.0603	0.057	0.096	0.5522	2.904	11.195	0.7954	-0.036	0.155	0.8183
Role-emotional (RE)	-0.680	0.761	0.3716	-0.058	0.095	0.5433	5.376	11.151	0.0227	-0.104	0.155	0.5024
Mental health (MH)	-0.514	0.766	0.5028	0.012	0.096	0.8992	-1.449	11.241	0.8975	-0.002	0.156	0.9877

eGFR, estimated glomerular filtration rate; MMSE, Mini-Mental State Examination. S.E., standard error.

*Statistical significance with Bonferroni correction, P < 0.0125.

† A lower eGFR per 30 mL/min/1.73 m2 indicates much worsened renal function in the early and moderate stages of chronic kidney disease.

Fig 1

Global Mini-Mental State Examination (MMSE) score by age, sex, and chronic kidney disease (CKD) stages.

Fig 2

Each category of Mini-Mental State Examination (MMSE) score by age, sex, and chronic kidney disease (CKD) stages.

Fig 3

Quality of life questionnaires by age, sex, and chronic kidney disease (CKD) stages.

Table 4

Comparison of different models for the relationship among eGFR estimates, MMSE, and quality of life.

Models (N = 497)	Model 1 (unadjusted)			Model 2 (adjusted for age, sex, and age × sex)			Model 3 (adjusted for age, sex, age × sex, education years)			Model 4 (adjusted for age, sex, age × sex, education years, HbA1c, and HDL-C)
eGFR (per 30 mL/min/1.73 m² lower†)	β	S.E.	P value	β	S.E.	P value	β	S.E.	P value	β	S.E.	P value
Global MMSE	-1.180	0.230	<0.0001*	-0.963	0.239	<0.0001*	-0.922	0.228	<0.0001*	-0.807	0.235	0.0007*
Orientation to time	-0.192	0.042	<0.0001*	-0.161	0.456	0.0004*	-0.159	0.046	0.0005*	-0.155	0.047	0.0011*
Orientation to place	-0.017	0.028	0.5433	-0.014	0.030	0.6299	-0.013	0.030	0.6721	-0.001	0.031	0.7835
Registration	-0.040	0.021	0.0645	-0.043	0.024	0.0685	-0.042	0.023	0.0750	-0.038	0.024	0.1152
Calculation	-0.475	0.101	<0.0001*	-0.397	0.109	0.0003*	-0.383	0.106	0.0003*	-0.338	0.109	0.0020*
Memory recall	-0.178	0.059	0.0027*	-0.106	0.063	0.0929	-0.101	0.062	0.1068	-0.084	0.064	0.1953
Language	-0.011	0.013	0.4297	-0.007	0.015	0.6566	-0.001	0.015	0.6675	-0.001	0.015	0.8341
Repetition	-0.040	0.023	0.0800	-0.030	0.025	0.2317	-0.030	0.025	0.2387	-0.024	0.026	0.3540
Complex commands	-0.228	0.077	0.0035*	-0.205	0.082	0.0132	-0.188	0.077	0.0150	-0.156	0.079	0.0494
Quality of life
Role-physical (RP)	-2.387	0.687	0.0006*	-2.332	0.756	0.0023*	-2.301	0.757	0.0024*	-2.219	0.779	0.0046*
Vitality (VT)	-1.480	0.691	0.0327	-1.815	0.758	0.0170	-1.784	0.757	0.0189	-1.929	0.777	0.0134
Social functioning (SF)	-1.339	0.690	0.0530	-1.438	0.764	0.0603	-1.421	0.764	0.0635	-1.403	0.781	0.0730
Role-emotional (RE)	-0.686	0.692	0.3217	-0.680	0.761	0.3716	-0.654	0.760	0.3905	-0.809	0.784	0.3023
Mental health (MH)	-0.204	0.695	0.7693	-0.514	0.766	0.5028	-0.493	0.766	0.5199	-0.896	0.773	0.2472

eGFR, estimated glomerular filtration rate; MMSE, Mini-Mental State Examination. S.E., standard error.

*Statistical significance with Bonferroni correction, P < 0.0125.

†A lower eGFR per 30 mL/min/1.73 m2 indicates much worsened renal function in the early and moderate stages of chronic kidney disease.

Validation study with partial least squares procedures

The Spearman’s correlation coefficients for all explanatory variables are listed in S2 Table). While all items in the MMSE were very weakly correlated, except for the weak association between calculation and complex commands (ρ = 0.374), all dimensions in SF-12 were weakly correlated, except for the moderate association between vitality and mental health (ρ = 0.566). The results of the validation study are listed in Table 5. Using PLS regression with PCR, we extracted two principal component factors from the dimensions of the MMSE and quality of life questionnaire. Factors 1 and 2 accounted for 2.3% and 0.5% of the total variation in eGFR (the dependent variable), respectively. Compared with Factor 1, Factor 2 was very weak in explaining the variation in eGFR. Factors 1 and 2 accounted for 23.5% and 18.2% of the total variation in the PCR model effects, respectively. For Factor 1, the independent variables orientation to time (0.337), orientation to place (0.397), registration (0.324), calculation (0.318), and complex commands (0.354) had factor loadings of >|0.3| and were significant in explaining the variation in eGFR. In contrast, for factor 2, the independent variables RP (0.397), VT (0.411), SF (0.339), RE (0.394), and MH (0.409) had high factor loadings, and they were very weak in explaining the variation in eGFR. These results are compatible with our findings from GLMMs.

Table 5

Validation with partial least squares (PLS) procedures.

Methods of PLS Procedures	Principle component regression
	Factor 1	Factor 2
Percent Variation Accounted for by Principal Components (%)
Model effects	23.475	18.171
Dependent variables of eGFR	2.309	0.478
Model effect loadings
Age	-0.154	-0.000
Orientation to time	0.337*	-0.201
Orientation to place	0.397*	-0.241
Registration	0.324*	-0.182
Calculation	0.318*	-0.047
Memory recall	0.261	-0.066
Language	0.296	-0.282
Repetition	0.165	0.031
Complex commands	0.354*	-0.136
Role-physical (RP)	0.207	0.397*
Vitality (VT)	0.224	0.411*
Social functioning (SF)	0.150	0.339*
Role-emotional (RE)	0.188	0.394*
Mental health (MH)	0.200	0.409*

*Variables with a factor loading of > |0.3| were considered significant.

Discussion

In this study, we investigated multiple domains of cognitive function and quality of life among community-based healthy older adults with early CKD. Participants with early CKD stages 3a and 3b had poor orientation to time, calculation, and executive function, and lower scores for physical status in the SF-12. Memory function showed no overt impairment in early CKD. The study results expand the previous findings [27, 33] that executive function deficits are evident earlier in the CKD illness at stage 3, and patients with late CKD stages 4–5 with poorer orientation in the older Han Chinese population. We found impaired executive function in the early stage of CKD (stages 3a and 3b), and global cognition impairment was accompanied by life dissatisfaction with RP and VT in early CKD stages 3a and 3b. This suggests that early intervention for cognitive assessment should be conducted in CKD stages 3a and 3b in older Han Chinese adults.

The speculative causes for the association between cognitive impairment and renal function deterioration were grouped into four categories: demography, clinical characteristics, dialysis procedures, and vascular factors [15–17, 69–71]. First, demographic contribution should not be a single factor to explain cognitive impairment in our participants with early stage of CKD. After adjustment for age and sex in models 2–4, the GLMMs showed that a lower eGFR was independently associated with cognitive impairment. Second, clinical factors did not explain the differences in cognitive impairment among the CKD groups. Third, none of the participants with CKD stages 3a and 3b received hemodialysis. This confirms the rebuttal association between cognitive impairment and hemodialysis [72]. Fourth, we considered that vascular factors also contributed to the causes of cognitive impairment in our early CKD participants (stages 3a and 3b). Vascular factors have been reported to be implicated in frontal-temporal lobe injury in early CKD, including interference with orientation and executive dysfunction [73, 74]. Unsurprisingly, therefore, our analysis supported the presence of cognitive impairment in the early to moderate stages of CKD in Han Chinese older adults. Our results are consistent with an earlier systematic review [29] that suggested that cognitive impairment exists across all stages of CKD, independent of the aging effect.

For quality of life assessment, our participants showed no obvious deficits in vitality, social functioning, emotional role, and mental health, except for physical role function. Our analysis was mostly consistent with a recent study [42] employing the EQ-VAS, which showed impaired self-perceived quality of life in patients at CKD stages 3a, 3b, and 4 before and after adjusting for sociodemographic factors. However, the EQ-VAS is a multifactorial scale, which was scored by asking the participants to indicate their health state in a range from 0 (worst) to 100 (best). Additionally, our results are similar to those of another study [40] using the SF-8, which showed worse physical component scores before adjustment for age and medical comorbidities in all stages of CKD. On the other hand, our assessment of quality of life is incompatible with a study [41] assessing quality of life using the CASP-19 scale. We considered that the dimensions of quality of life measured by the SF-12 and CASP-19 scales are different. The CASP-19 is much focused on self-completion, pleasure, and control [75].

Compared to previous studies, our study has the following key characteristics: First, previous analysis found unclear which is the best method for assessing eGFR in elderly and cognitively impaired adults [32, 60]. Since we enrolled a monoethnic Chinese population, we could manage this problem by employing the BIS equation. Our conclusion is consistent with previous studies [29, 32, 33] using the MDRD and CKD-EPI equations in different ethnic and age groups. Second, our analysis included covariates of demography, sociodemographic factors, and medical comorbidities in terms of laboratory tests. Third, we performed the analysis in both genders, unlike some studies with only men [76] and women [35, 77]. An earlier study in Taiwan [35] included only midlife women in Kinmen, a group of islands off the southeastern coast of mainland China, governed as a county in Taiwan. Fourth, our nationwide sampling should have a representative population of Han Chinese. We performed a comprehensive door-to-door survey conducted by trained interviewers and laboratory examinations. Fifth, we validated the study results using the unconventional method of partial least squares regressions with principal components to investigate the factor loadings on the response variable of eGFR. Factor loadings on orientation, calculation, and complex domains were all > 0.3, which is consistent with the analysis of GLMMs. Sixth, cognition and quality of life were assessed in our study.

The study has some limitations. First, our study design involved a cross-sectional design, which cannot be used to infer the cause-effect relationship. Since this study was part of a large-scale nationwide nutrition survey, more advanced biomarkers or imaging studies were unavailable for our data collection. Second, despite being the most widely used instrument in the extant literature, the MMSE is known to be affected by ceiling and floor effects in different languages and populations [29, 78, 79]. While the ceiling effect indicates that the performance of MMSE, independent of cognitive state, is favorably affected by highly educated level, the floor effect suggests that performance is adversely affected by poor education [78]. In addition, the MMSE is also known to be less sensitive to mild changes in cognition, and therefore may have reduced sensitivity for early CKD stages [29]. These could limit the generalizability and comparability of similar studies. Some studies [80, 81] indicated that the Montreal Cognitive Assessment (MoCA) showed better utility as a tool for assessing patients with CKD. Third, we did not assess severe cardiovascular diseases or other neurological disorders in our study. Since the NAHSIT 2013–2016 primarily focused on healthy older adults in adults, only comorbidities of hypertension, hyperlipidemia, and diabetes mellitus were assessed in our study.

Our study confirmed that CKD with cognitive impairment (especially the domains of orientation, calculation, and complex commands) is present in the early to moderate illness stages. A non-invasive behavior intervention by cognitive remediation (CR) is proposed to help promote neuroplastic change and enhance cognitive performance in patients with CKD [82]. Different CR approaches [83] can be tailored to specific cognitive deficits in patients with CKD. On the other hand, pharmacological intervention with erythropoietin, a hormone used for the treatment of renal anemia, showed possible neuroprotective effects in animals [84, 85] and human studies [86, 87]. Other agents, such as cholinesterase inhibitors, have been used in patients with Alzheimer’s disease [88] and vascular dementia [89], but not specifically for CKD patients. However, to date, there has been a shortage of behavioral interventions and pharmacological research on cognitive improvement in CKD patients [82].

Conclusions

In conclusion, this nationwide, community-based, cross-sectional study in healthy older adults confirmed that early CKD (stages 3a and 3b) is associated with cognitive decline in the global MMSE and domains of orientation to time, calculation, and complex commands for the elderly Han Chinese population. More attention should be paid to healthy older adults with early stage CKD with physical role function deficits in quality of life. A prospective cohort study with a longer follow-up period might provide more evidence regarding the cause-effect relationship and thus enable a clearer understanding of the nature of the relationship. Strategies to manage cognitive impairment and improve quality of life can be implemented accordingly.

Mini-Mental State examination and quality of life assessment stratified by sex.

(DOCX)

Click here for additional data file.

Spearman correlation coefficients among all items of the Mini-Mental State examination and SF-12.

(DOCX)

Click here for additional data file.

17 Aug 2021

PONE-D-20-31145

Quality of Life and Cognitive Assessment in Healthy Older Asian People with Early Chronic Kidney Disease: the NAHSIT 2013–2016 and Validation Study

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Reviewer #1: “Quality of Life and cognitive assessment in healthy older Asian people with early chronic kidney disease: the NAHSIT 2013-2016 and validation study.”: Investigators intended to study the association between kidney function and cognition, as well as quality of life. The study is based on data from the NAHSIT dataset. Authors concluded that CKD stages 3 (a and b) is associated with cognitive decline in multiple domains, and that these patients have physical complaints.

The paper requires editing for English, for clarification of meaning.

Abstract

Purpose of the study is not stated.

Need to mention study is Taiwan-based.

In methods, need to mention this is data from NAHSIT 2013-2016.

Also it says “…categorized into three CKD groups”… but they spell out 4 groups.

Authors refer to those in stages 3 as “early CKD”; those would be patients with “moderate” disease.

In conclusion, “multiple cognitive decline”, “More attention for cognition should be paid for healthy older adults perceiving dissatisfaction on physical status”: unclear what these mean.

Introduction

-1st paragraph (prg): authors refer to USRDS annual report but don’t cite it.

-The introduction is inadequate; the argument for the study is weak.

-The specific aim/hypothesis need to be rewritten (in line with design) for clarity.

-Literature on cognition and CKD is not substantiated, despite the availability of important existing literature (such as with various tests of cognition performed on the Chronic Renal Insufficiency Cohort).

-Authors do not make the case for studying quality of life (QOL).

-Unclear why only “physical disability” and “caregiver burden” are highlighted.

Methods

-“systemic sampling”: do authors mean “systematic”?

-Authors need to clarify if this is a secondary analysis of data (2013-2016 of NAHSIT); otherwise, are they reporting primary data collection on MMSE/SF-12 as an add-on (to NAHSIT) conducted in those years?? This needs to be clear. What was the main aim of constructing the primary dataset?

-Authors report this to be a “cross-sectional” study; need to clarify if all participant data were collected in only one visit.

-Data collection: clarify that this was for the primary study. Unclear how lab results on glucose and lipids, methodology on BP measurement are relevant in the context of this work. It would be helpful instead to elaborate on sociodemographic data for the current study.

-There is very limited description of measurement tools (MMSE, SF-12) pertinent to main study variables; additional details are needed such as SF-12 scoring and interpretation, applicability in Asian population, other.

-The use of Berlin Initiative Study equation for GFR estimation is not mainstream; authors did not elaborate on its applicability in Asian populations. Authors haven’t explained why those in stages 4 and 5 are grouped into one category. In labeling patients in stages 1 and 2 of CKD, how the diagnosis was made in addition to eGFR needs to be clarified.

-Statistical analysis: Elaboration is needed on the use of GLMM in this cross-sectional study. Authors need to clarify “covariates” used in the modeling, instead of referring to them as independent variables. The validation approach using principal component regression (factors 1 and 2, with dependent variable of eGFR) is unclear.

Results

-How was the 30-point change in eGFR coined in the study?

-In table 4, why does model 4 include HbA1C and HDL?

-Validation study and results depicted in figures (depicting outcomes by age, sex)… are not in line with study purpose (there are no Specific Aims to support the conduct of those analyses).

Discussion and Conclusion:

-The word “begin” would relate to longitudinal studies; its use should be reconsidered in this paper.

-Discussion/conclusion will require revision based on revisions in previous sections.

-Unclear what is meant by “feeling physical disturbance” in conclusion.

Reviewer #2: The authors report on a large nationwide study of cognitive impairment and quality of life in CKD patients 65 years and above. There are a couple of areas that can be improved, particularly in terms of study rationale, terminology and phrasing of interpretations, which currently reduce my enthusiasm for this manuscript.

Line 31-32: Merge CKD stages 1 and 2 to match the statement that 3 groups were derived. At present it reads as 4 separate groups.

The Introduction itself is short and lacking on details that contribute to a well-supported study rationale. In particular, the authors have not provided any evidence from previously published papers showing that cognitive impairment is related to eGFR levels (see Etgen T et al Chronic kidney disease and cognitive impairment: a systematic review and meta-analysis. Am J Nephrol. 2012;35(5):474–82), which would support the notion that cognitive impairment would be present in early as well as late stage CKD. In fact, this is evidenced in the Berger et al. 2016 systematic review and meta-analysis which the authors cite in the Discussion. Furthermore, in another systematic review (Brodski, J. et al. (2019). A Systematic Review of Cognitive Impairments Associated With Kidney Failure in Adults Before Natural Age-Related Changes. Journal of the International Neuropsychological Society, 25(1), 101-114.), it has been shown that the cognitive impairments found in relation to CKD are independent of age-related cognitive decline, and incrementally increase as the stages of CKD advance. At the very least, these key reviews/meta-analyses should be cited to support the argument for the authors investigating cognition in early-stage CKD, even if within and despite an older cohort.

The Introduction is also lacking in any background information to support an investigation of quality of life within a CKD sample. Please add this information.

Based on the existing information in the literature, once added to the Introduction, the authors should revise the hypotheses to be a bit more specific. I would also recommended a statement of aims to cover the components of the proposed analyses.

The authors are further requested to clarify and provide a rationale for the validation study within the Introduction section. At present, it appears abruptly.

Was information about co-morbid conditions (e.g. diabetes, cardiovascular disease, neurological disorders/conditions)? There is a sizeable literature showing cognitive impairments associated with these conditions, which need to be considered for the current dataset. If this information was not collected, it is a major limitation of the study and needs to be mentioned in text.

Given the number of analyses conducted, correction for multiple comparisons (e.g. Bonferroni correction) in the group comparisons is required to minimise Type 1 error.

Participant group characteristics could be reported in a table for greater clarity and ease of comprehension.

It is not appropriate to say that MMSE scores decreased between stages as the participants were not followed up longitudinally. As what has been conducted are just group comparisons, the differences should be described as performance differences between groups of patients at the different stages. The use of ‘decreasing’ is misleading in this context of reporting group comparison results. In addition, within the adjusted GLMMs, it should also be phrased similarly (e.g. lower eGFR is associated with reduced QOL). Please amend throughout.

In line 205, please refrain from using terminology such as ‘thoroughly investigated’ when many cognitive domains were not assessed in this study.

In lines 210-211, it is not accurate to say that “patients of late CKD stages 4–5 with poorer orientation, executive function begin in the early stage of CKD (stages 3a and 3b)” as the authors did not longitudinally follow a group of patients as their CKD progressed. I believe the authors are suggesting that executive function deficits are present earlier in the illness at Stage 3, so it would be more accurate to just say that executive function deficits are evident from Stage 3 CKD.

In line 220, increasing age and female sex cannot promote cognitive impairment, rather they can be associated with greater cognitive impairment. Please rephrase.

In line 224, it would be better to say that clinical factors do not really explain the differences in cognitive impairment between the groups.

Line 230-232: It is not intuitive how the authors arrived at the conclusion that their analysis “analysis supported the association between early renal function impairment and cognitive impairment should not be the confounding effect of aging only” based on the statement preceding it. Please clarify. In addition, such a conclusion has previously been reached in the literature (Brodski et al, 2019). Relatedly, the authors should better integrate and situate their findings in relation to the existing literature.

Line 234-242: It is unclear how this paragraph fits within the narrative.

Regarding limitations, the authors should also discuss the limits of using the MMSE for assessing cognitive function within CKD (see Brodski et al, 2019). Also see my earlier point about premorbid conditions.

The authors should also briefly discuss the utility of cognitive remediation to address cognitive deficits, particularly in early CKD (see Tan, E. J. et al (2019). Considering the utility of cognitive remediation therapy in chronic kidney disease. Clinical and Experimental Nephrology.) for some points. This would help better contextualise the current findings.

Please review the manuscript for grammatical errors throughout.

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Reviewer #1: No

Reviewer #2: No

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16 Sep 2021

We thank the reviewers for their constructive comments. We have revised the manuscript to address all the questions and comments raised by the three reviewers. We highlight the changes made to the original version by setting the text color to red. Our specific responses to each comment are as follows:

Responses to reviewer #1:

“Quality of Life and cognitive assessment in healthy older Asian people with early chronic kidney disease: the NAHSIT 2013-2016 and validation study.”: Investigators intended to study the association between kidney function and cognition, as well as quality of life. The study is based on data from the NAHSIT dataset. Authors concluded that CKD stages 3 (a and b) is associated with cognitive decline in multiple domains, and that these patients have physical complaints.

�  The paper requires editing for English, for clarification of meaning.

• We are grateful for all the constructive comments. We have worked with an English editing service and have revised our manuscript accordingly.

Abstract

�  Purpose of the study is not stated.

• We revised the manuscript to address the purpose of the study: “We sought to obtain an overview and the attributable effect of impaired glomerular filtration on multiple domains in cognition and dimensions of quality of life for community-based healthy older adults in Taiwan. (Please see the Abstract section, page 2, Line 25-28)

�  Need to mention study is Taiwan-based.

• We revised the manuscript by mentioning that this study is a nationwide cross-sectional survey of older adults in Taiwan. (Please see the Abstract section, Page 2, Line 32).

�  In methods, need to mention this is data from NAHSIT 2013-2016.

• We added the description “The study data were derived from the Nutrition and Health Survey in Taiwan (NAHSIT) 2013–2016.” (Please see the Abstract section, Page 2, Line 29-30)

�  Also it says “…categorized into three CKD groups”… but they spell out 4 groups.

• We revised the text to say “Participants were categorized into four chronic kidney disease (CKD) groups.” (Please see the Abstract section, Page 2, Line 31).

�  Authors refer to those in stages 3 as “early CKD”; those would be patients with “moderate” disease.

• According to the definition by the National Kidney Foundation (NKF) Kidney Disease Outcomes Quality Initiative (KDOQI)[1] and the International Kidney Disease Improving Global Outcomes (KDIGO) guidelines [2], stages 3a (eGFR of 45–59 mL/min/1.73 m2), and 3b (eGFR of 30–44 mL/min/1.73 m2) of CKD indicate moderately impaired eGFR.

• Stage 3 CKD (including 3a and 3b) are the first stages that could be identified by blood tests of creatinine alone. From the viewpoint of clinical management and policy level, a systematic review[3] concluded that Stage 3 CKD of mild to moderate impaired eGFR could be regarded as “early” CKD. A previous longitudinal study[4] showed that approximately half of patients with Stage 3 CKD progressed to late stages 4 and 5. Additionally, we found some relevant studies[5, 6] which defined Stages 3 as “early stages.”

• In our revised manuscript, we followed the reviewer’s advice and designated Stage 3 as a “moderate” stage to improve readability. Accordingly, the title was revised as “Quality of Life and Cognitive Assessment in Healthy Older Asian People with Early and Moderate Chronic Kidney Disease: the NAHSIT 2013–2016 and Validation Study.” (Please see page 1, title; page 2, line 36, Abstract section)

�  In conclusion, “multiple cognitive decline”, “More attention for cognition should be paid for healthy older adults perceiving dissatisfaction on physical status”: unclear what these mean.

• In this study, we investigated both “quality of life” and “cognition” in older adults with early and moderate stages of CKD. We found that participants with stage 3 CKD manifested role-physical and vitality deficits in the dimensions of quality of life, and that participants with stage 3 CKD exhibited cognitive deficits in the domains of orientation to time, calculation, and complex commands. Therefore, participants had subjective deficits in role-physical behavior. To improve readability, the conclusion was revised as follows: “Elderly Han Chinese adults with moderately impaired renal filtration could manifest cognitive deficits in orientation to time, calculation, and impaired quality of life in physical-role functioning.” (Please see page 2, Line 43-45)

Introduction

�  -1st paragraph (prg): authors refer to USRDS annual report but don’t cite it.

• The citation of the reference “USRDS annual report 2020” was added[7]. (Please see page 4, line 53, Introduction section)

�  -The introduction is inadequate; the argument for this study is weak.

• In our revised manuscript, we substantiate the introduction by adding five relevant subsections as follows: (1) high prevalence of chronic kidney disease in Taiwan, (2) measures of chronic kidney disease, (3) cognitive impairment in chronic kidney disease, (4) quality of life in chronic kidney disease, and (5) study rationale and aims. In the first two sections, we accentuated the high prevalence of CKD in Taiwan and how kidney filtration rates were estimated in older adults. Thereafter, we summarized the current literature investigating the associations among cognitive impairment, quality of life, and worsened renal function. The study rationale has been revised accordingly. (Please see Page 3-6, Line 49-119, introduction)

�  -The specific aim/hypothesis need to be rewritten (in line with design) for clarity.

• We revised the hypotheses and specific aims as follows: We hypothesized that the high prevalence of cognitive impairment in older adults with early CKD in Taiwan, and the perception of the physical and mental well-being of older adults was worsened in the early stages of CKD. We aimed to (1) obtain an overview of cognitive impairment and quality of life in each stage of CKD, and (2) to assess the attributable effect of poor kidney filtration function on multiple cognitive domains dimensions of quality of life among community-based healthy older adults in Taiwan in this nationwide cross-sectional study. (Please see page 6, Lines 122-140, Introduction)

�  -Literature on cognition and CKD is not substantiated, despite the availability of important existing literature (such as with various tests of cognition performed on the Chronic Renal Insufficiency Cohort).

• In our revised manuscript, we substantiated the important existing literature. First, we introduced the pathophysiology of impaired renal filtration and cognition. Second, we reported that a vast majority of existing studies focused on reporting dementia in the late stages of CKD. Third, we listed the studies of systematic review and meta-analysis, which indicated that impaired eGFR is independently associated with increased MCI. Finally, we reviewed the relevant literature on investigating cognition in the early stages of CKD. (Please see Page 4-5, Line 73-101, introduction)

�  -Authors do not make the case for studying quality of life (QOL).

• In our revised manuscript, a new section for existing literature of “quality of life (QoL) and CKD” was added. We have cited and summarized these relevant studies, including a systematic review of QoL in late CKD stages, and the few available studies which enrolled participants in early CKD stages. In our review, whether quality of life was disturbed in the early stages of CKD remains undefined. There is also a lack of relevant research on ethnic Han Chinese. (Please see page 5, Line 103-119, introduction)

�  -Unclear why only “physical disability” and “caregiver burden” are highlighted.

• We revised our description to improve the readability of the study rationale and aims. In the first version of the manuscript, we emphasize that participants with early CKD may suffer from deficits in the perception of physical well-being and accentuate the caregiver’s burden. In addition, there is a high prevalence of CKD and ESRD and an increasing aging population in Taiwan. In our revised manuscript, the study rationale and aims have been rewritten to improve readability. (Please see page 6, Line 122-140, introduction)

Methods

�  -“systemic sampling”: do authors mean “systematic”?

• Thank you for your comment. We have revised the word to “systematic.” (Please see page 7, line 149, introduction).

�  -Authors need to clarify if this is a secondary analysis of data (2013-2016 of NAHSIT); otherwise, are they reporting primary data collection on MMSE/SF-12 as an add-on (to NAHSIT) conducted in those years?? This needs to be clear. What was the main aim of constructing the primary dataset?

• The study design and data collection in NAHSIT 2013–2016 were cited[8]. First, we declared this as a secondary analysis of original data from NAHSIT 2013 to 2016. The content of the primary survey included (1) behavioral indicators, such as MMSE and SF-12; (2) health outcome indicators, such as cardiovascular disease, kidney disease; and (3) laboratory tests of clinical chemistry, such as serum creatinine, lipid profiles, and blood glucose. Therefore, the MMSE and SF-12 data were collected during the study period 2013-2016 and these were not add-on variables. (Please see page 7, Line 151-157, Methods section)

• In addition, the primary aim of conducting NAHSIT by the Health Promotion and Administration, Ministry of Health and Welfare in Taiwan is to determine the nutritional status of the Taiwanese population, which was used as a reference for nutrition and health policy making in a government entity. (Please see page 7, Line 146-149, Methods section)

�  -Authors report this to be a “cross-sectional” study; need to clarify if all participant data were collected in only one visit.

• In our revised manuscript, we added the statement “All participants were visited once during the study period.” (Please see page 8, Line 155-156, Methods section)

�  -Data collection: clarify that this was for the primary study. Unclear how lab results on glucose and lipids, methodology on BP measurement are relevant in the context of this work. It would be helpful instead to elaborate on sociodemographic data for the current study.

• We clarified that data collection was for the primary objective of the study. (Please see page 8, Line 158, Method section)

• In our literature review, we found that diabetes increased the risk of cognitive impairment[9, 10] and an association between hyperlipidemia and mild cognitive impairment[11, 12].Therefore, we collected data on glucose and lipids, which were used for covariate adjustment in the multivariable regression models.

• The only sociodemographic information available to us was educational level and individual income in the four CKD groups. In our analysis, we found no statistically significant differences in individual income among the four stages of CKD; however, years of education were significantly lower in the moderate and late stages of CKD. (Please see page 12, Lines 279-280, Results section; Table 1)

�  -There is very limited description of measurement tools (MMSE, SF-12) pertinent to main study variables; additional details are needed such as SF-12 scoring and interpretation, applicability in Asian population, other.

• The culturally adapted traditional Chinese version of the Mini-Mental State examination (MMSE)[13] and SF-12 are the most widely used tools for assessing cognition and generic quality of life, respectively. We have added more detailed information regarding the measurement tools.

• The traditional Chinese version of the MMSE includes questions on orientation to time (5 points), orientation to place (5 points), registration (3 points), calculation (5 points), memory recall (3 points), language (2 points), repetition (1 point), and complex commands (6 points), and the MMSE score ranges from 0 (worst) to 30 (best).[14, 15] For the Taiwanese population, the norms[16] indicated 2 cutoff scores for determining cognitive impairment: a value of < 27 for literate individuals and another value of < 16 for the illiterate, respectively

• The most well-validated tool for quality of life assessment for the Taiwanese population is the traditional Chinese version of the SF-36[17, 18]. Despite being valid and equivalent for Han Chinese and other ethnic groups, SF-36 is limited by its length and time-consuming characteristics. The traditional Chinese version of SF-12, an abbreviated form of SF-36, is validated as equivalent to SF-36 for assessing the dimensions of physical and mental health.[19] The questionnaire of SF-12 questionnaire includes five dimensions of concepts: role-physical (RP), vitality (VT), social functioning (SF), role-emotional (RE), and mental health (MH). Each concept is directly transformed into a scale ranging from 0 to 100, with a mean distribution of 50 and a standard deviation of 10. A higher score signifies a better health state.[20, 21] (please see Page 7-8, Lines 165-185, Methods section)

�  -The use of Berlin Initiative Study equation for GFR estimation is not mainstream; authors did not elaborate on its applicability in Asian populations. Authors haven’t explained why those in stages 4 and 5 are grouped into one category. In labeling patients in stages 1 and 2 of CKD, how the diagnosis was made in addition to eGFR needs to be clarified.

• In our revised manuscript, we cited two studies[22, 23] which concluded that eGFR derived from the Berlin Initiative Study (BIS) equation achieved superior accuracy and lower rates of misclassification of CKD stages compared to the CKD-EPI and MDRD equations in older Chinese adults. These studies[22, 23] compared the different equations, including the Modification of Diet in Renal Disease (MDRD) equation, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, and the BIS equation, to derive accurate eGFR (with 99mTc-DTPA as the standard method) in the Han Chinese population. (Please see page 9, Line 204-210, Methods section)

• In our revised manuscript, we added an explanation as to why those in stages 4 and 4 are grouped, as follows: “Since the NAHSIT 2013–2016 was expected to enroll healthy older adults, the number of late CKD Stages 4 to 5 was expected to be small, and therefore Stages 4 and 5 were grouped into one category.” (Please see page 9, Line 216-218, Methods section)

• In addition to eGFR, we confirmed the early and moderate stages of CKD using the urine albumin-to-creatinine ratio (ACR). Impaired renal function allows albumin to pass into the urine. According to the international guideline group Kidney Disease Improving Global Outcomes (KDIGO) guidelines[2], urine ACR< 30 mg/g is defined as normal to mildly increased albuminuria, urine ACR of 30–300 mg/g as moderately increased albuminuria, and urine ACR >300 as severely increased albuminuria. (Please see Page 9-10, Line 219-222)

• The corresponding urine ACR values for all four groups are listed in Table 1. (Please see page 13-14, Table 1).

�  Statistical analysis: Elaboration is needed on the use of GLMM in this cross-sectional study. Authors need to clarify “covariates” used in the modeling, instead of referring to them as independent variables. The validation approach using principal component regression (factors 1 and 2, with dependent variable of eGFR) is unclear.

• We described this model in the following matrix formula Yi = Xi β + Ri + Ei, where Yi denotes the matrix containing a set of measures of all items of the MMSE and SF-12 on the ith older adult participant as dependent variables, Xi denotes the matrix containing a set of intercepts, independent variables of eGFR (per 30 mL/min/1.73 m2), and the covariates of age, sex, education years, and the characteristics that were imbalanced among the four CKD groups; β denotes the vector of estimated regression parameters; Ri denotes an intercept random effect associated with the ith older adult participant, which has a normal distribution and is independent and identically distributed (i.i.d.), where Ei denotes random error. (Please see page 10, Line 233-240, methods section)

• The covariates used in the GLMMs were none (model 1), a set of variables with age, sex, and interaction of age and sex (model 2), a set of variables with age, sex, and interaction of age and sex, and education years (model 3), and a set of variables with age, sex, and interaction of age and sex, education years, and the characteristics that were imbalanced among the four CKD groups (Model 4). (Please see page 10, Line 240-244, Methods section)

• Validation using principle component regression is elaborated as follows. To verify the association between renal function injury, cognitive impairment, and quality of life, we swapped the factors of eGFR in older adults and measured all items of the MMSE and SF-12 in the regression analysis. Conventionally, all items of the MMSE and SF-12 have been employed as dependent variables (or response variables), and eGFR has been used as an independent variable (or explanatory variable). Instead, we conducted partial least squares (PLS) regressions with the following formula: Y = XB + B0, where Y denotes the response matrix of eGFR, X denotes the factor matrix of all items of the MMSE and SF-12, B denotes the matrix of factor loadings, and B0 denotes error terms. Spearman’s rank correlation tests were used to examine the correlations among all items of the MMSE and SF-12. One major advantage of PLS regression is that it can easily manage the multicollinearity problem in conditions when there are numerous highly correlated explanatory variables[60, 61]. PLS regressions can help identify the optimal linear combinations of explanatory variables by projecting them to new spaces. The PLS regression was performed using the PROC PLS procedure implemented in SAS 9.4 software, with a factor number of 2 and principal components regression (PCR) to obtain factor loadings. (Please see page 11, Line 252-266, Methods section)

Results

�  -How was the 30-point change in eGFR coined in the study?

• According to the definition by the National Kidney Foundation (NKF) Kidney Disease Outcomes Quality Initiative (KDOQI)[1] and the International Kidney Disease Improving Global Outcomes (KDIGO) guidelines [2], CKD stage 1 was defined as eGFR >90 mL/min/1.73 m2, CKD stage 2 with eGFR of 60–89 mL/min/1.73 m2, and CKD stage 3 with eGFR of 30–59 mL/min/1.73 m2.

• Accordingly, the difference in eGFR between the early and moderate CKD stages is 30-point. A lower eGFR per 30 mL/min/1.73 m2 indicates a much worse renal function in the early and moderate stages of chronic kidney disease. In our revised manuscript, we have added this description to the footnotes of Table 3-4. (Please see Page 18-19, Table 3-4, Results section)

�  -In table 4, why does model 4 include HbA1C and HDL?

• In Table 1, we provide an overview of the characteristics of the four CKD stages. In our revised manuscript, we mentioned that in model 4, the characteristics or covariates that were imbalanced (P < 0.05), and the serum levels of HbA1c (P = 0.0430) and HDL-C (P = 0.0003) were not homogenous among the four groups of CKD; however, the mean HbA1c and HDL-C levels were within normal limits. (Please see Page 10, Line 244; Page 10, Methods; Page 13-14, Table 1, Results section)

�  -Validation study and results depicted in figures (depicting outcomes by age, sex)… are not in line with study purpose (there are no Specific Aims to support the conduct of those analyses).

• Our validation rationale is as follows: A validation study was used to examine the robustness of the association between eGFR, cognitive impairment, and quality of life. There was likely a high degree of collinearity in our data analysis, since multiple domains of cognition and multiple dimensions of life quality were assessed. We therefore replaced the conventional regression models with partial least squares (PLS) regressions to deal with potential collinearity and confirm robustness. (Please see Page 6, Line 135-140, Introduction; Page 11, Line 259-261, Methods section)

• Our aim was to use PLS regression to deal with possible collinearity. In our data analysis, we noticed weak collinearity of all items of the MMSE and SF-12. While all items in the MMSE were very weakly correlated, except for the weak association between calculation and complex commands (ρ = 0.374), all dimensions in SF-12 were weakly correlated, except for the moderate association between vitality and mental health (ρ = 0.566). (Please see Page 20, Line 341-344, Results section)

Discussion and Conclusion:

�  -The word “begin” would relate to longitudinal studies; its use should be reconsidered in this paper.

• In our revised manuscript, we deleted the words “begin,” and “launch” in the Discussion section. The description was revised as “early intervention for cognitive assessment should be conducted in CKD stages 3a and 3b in Han Chinese Older adults.” (Please see Page 21-22, Lines 363-373)

�  -Discussion/conclusion will require revision based on revisions in previous sections.

• Based on the literature review and analysis, our discussion and conclusions have been greatly revised. We addressed the following key characteristics: First, we enrolled a monoethnic Chinese population and we could manage this problem by employing the BIS equation. Our conclusion is consistent with previous studies[24-26] using the MDRD and CKD-EPI equations in different ethnic and age groups. Second, we adjusted the important covariates of demographic and sociodemographic factors and comorbidity in terms of laboratory tests. Third, we performed the analysis in both genders, unlike some studies with only men[27] and women[28, 29]. An earlier study in Taiwan[29] included only midlife women in Kinmen, a group of islands off the southeastern coast of mainland China, governed as a county in Taiwan.

• Additionally, we addressed the limitation of employing the MMSE to assess cognitive function and premorbid conditions. The relevant discussion for quality of life in patients with CKD has been added. Lastly, we substantiated the discussion by adding possible behavioral interventions for CKD patients in further research. (Please see Page 22-25, Line 392-450)

�  -Unclear what is meant by “feeling physical disturbance” in conclusion.

• We are grateful for all the constructive comments. The conclusion was revised for clarity, as follows “More attention should be paid to healthy older adults with early stage of CKD having physical role function deficits in quality of life.” (Please see Page 25, Line 453-461)

Responses to reviewer #2:

�  The authors report on a large nationwide study of cognitive impairment and quality of life in CKD patients 65 years and above. There are a couple of areas that can be improved, particularly in terms of study rationale, terminology and phrasing of interpretations, which currently reduce my enthusiasm for this manuscript.

• We are grateful for all the constructive comments. In our revised manuscript, we have greatly revised the study rationale, terminology, and phrasing.

• In terms of rationale, Taiwan has the highest worldwide prevalence of CKD and ESRD [7]. Therefore, assessment of cognition in CKD is of paramount importance, and we hypothesized that the high prevalence of cognitive impairment in older adults with CKD in Taiwan, and perception of the physical and mental well-being of older adults was worsened in the early stages of CKD. We aimed (1) to obtain an overview of cognitive impairment and quality of life in each stage of CKD, and (2) to assess the attributable effect of poor kidney filtration function on multiple domains or dimensions of cognition and quality of life among community-based healthy older adults in Taiwan in this nationwide cross-sectional study. (Please see page 6, Line 122-140)

�  Line 31-32: Merge CKD stages 1 and 2 to match the statement that 3 groups were derived. At present it reads as 4 separate groups.

• Thank you for your comment. We revised the description into four groups: (1) CKD stage 1, (2) CKD stage 2, (3) CKD stages 3a and 3b, and (4) CKD stages 4 and 5. We merged CKD stages 4 and 5 into a single group due to the smaller sample size of late CKD stages in our community study. (Please see page 2, line 31).

�  The Introduction itself is short and lacking on details that contribute to a well-supported study rationale. In particular, the authors have not provided any evidence from previously published papers showing that cognitive impairment is related to eGFR levels (see Etgen T et al Chronic kidney disease and cognitive impairment: a systematic review and meta-analysis. Am J Nephrol. 2012;35(5):474–82), which would support the notion that cognitive impairment would be present in early as well as late stage CKD. In fact, this is evidenced in the Berger et al. 2016 systematic review and meta-analysis which the authors cite in the Discussion. Furthermore, in another systematic review (Brodski, J. et al. (2019). A Systematic Review of Cognitive Impairments Associated With Kidney Failure in Adults Before Natural Age-Related Changes. Journal of the International Neuropsychological Society, 25(1), 101-114.), it has been shown that the cognitive impairments found in relation to CKD are independent of age-related cognitive decline, and incrementally increase as the stages of CKD advance. At the very least, these key reviews/meta-analyses should be cited to support the argument for the authors investigating cognition in early-stage CKD, even if within and despite an older cohort.

• In our revised manuscript, we have expanded the contents of the Introduction section. We substantiated the content by adding five relevant subsections as follows: (1) high prevalence of chronic kidney disease in Taiwan, (2) measures of chronic kidney disease, (3) cognitive impairment in chronic kidney disease, (4) quality of life in chronic kidney disease, and (5) study rationale and aims.

• Accordingly, these important studies have been cited in our manuscript. We cited two meta-analyses by Etgen et al.[24] and Berger et al.[25] showed that impaired eGFR is associated with cognitive impairment and can be present in the early and late stages of CKD. A systematic review[26] included three relevant studies on CKD patients <65-year-old which found that these patients had slow processing speed[30], impaired verbal learning[29, 31], and impaired working memory[29] in moderate stages of CKD. Our argument has been revised. (Please see Page 3-6, Lines 48-140, introduction)

�  The Introduction is also lacking in any background information to support an investigation of quality of life within a CKD sample. Please add this information.

• We amended the introduction section and added background information to support an investigation of the quality of life of older Chinese adults with CKD as follows:

• The term “quality of life” can be traced back to the definition in 1948 by the World Health Organization (WHO) as a state of perception of “physical, mental, and social well-being, and not merely the absence of disease.[32]” Prior meta-analysis[33] assessing the utility-based quality of life with 12-item or 36-item Short Form Health Survey (SF-12 or SF-36), EuroQol Group’s EQ-5D, and other instruments suggested that dialysis is significantly associated with reduced quality for ESRD patients. However, few studies have investigated the association between quality of life and the early stages of CKD. We found that these studies exhibited inconsistent results: (1) a cross-sectional study enrolled ≥60 year-old participants in North California[34] showed no relationship between eGFR and quality of life scores in physical and mental dimensions after adjustment for medical comorbidities; (2) a cross-sectional study including ≥50 year-old Irish participants [35] showed that reduced scores in quality of life are associated with eGFR by serum cystatin rather than creatinine; and (3) a recent cross-sectional study[36] enrolled 2,255 older adults in European countries and found that early CKD at stages 3a and 3b, defined by the BIS equation, is associated with quality of life on EQ-Visual Analogue Scale (EQ-VAS). To our knowledge, there is a shortage of relevant research in the Chinese population. (Please see Page 5, Line 103-120, introduction section)

�  Based on the existing information in the literature, once added to the Introduction, the authors should revise the hypotheses to be a bit more specific. I would also recommended a statement of aims to cover the components of the proposed analyses.

• We revised the introduction section by adding existing literature investigating the association between cognition and CKD, and between quality of life and CKD. The specific aims of this study are as follows:

• In this study, we hypothesized that the high prevalence of cognitive impairment in older adults with CKD in Taiwan, and perception of the physical and mental well-being of older adults was worsened in the early and moderate stages of CKD. We aimed to (1) obtain an overview of cognitive impairment and quality of life at each stage of CKD in Han Chinese population, and (2) assess the attributable effect of poor kidney filtration function, after adjustment for demographic factors, on multiple cognitive domains and dimensions of quality of life among community-based healthy older adults in Taiwan in this nationwide cross-sectional study. (Please see page 6, Line 122-140, introduction section)

�  The authors are further requested to clarify and provide a rationale for the validation study within the Introduction section. At present, it appears abruptly.

• The rationale for conducting the validation study was as follows: The existence of collinearity in our data analysis was likely, since multiple domains of cognition and multiple dimensions of life quality were assessed. As a separate validation study, we employ partial least squares (PLS) regressions to solve potential collinearity and confirm the robustness of our results. (Please see Page 6, Line 135-140)

�  Was information about co-morbid conditions (e.g. diabetes, cardiovascular disease, neurological disorders/conditions)? There is a sizeable literature showing cognitive impairments associated with these conditions, which need to be considered for the current dataset. If this information was not collected, it is a major limitation of the study and needs to be mentioned in text.

• In our study, we assessed comorbid diabetes by measuring fasting glucose and HbA1c levels. According to the American Diabetic Association[37], participants were classified as having DM by fasting glucose ≥126 mg/dl or HbA1c level ≥6.5%.

• Hypertension is the only cardiovascular disease variable available to us. We defined participants with hypertension as systolic blood pressure systolic BP (SBP) of ≥140 mmHg or diastolic BP (DBP) of ≥90 mmHg, in accordance with the guidelines of the American Heart Association[38]. Otherwise, cardiovascular and neurological diseases were not assessed in the NAHSIT 2013–2016 (Please see Page 9, Line 197-201). We also mentioned this limitation in our discussion section. (Please see Page 24, Line 435-438)

�  Given the number of analyses conducted, correction for multiple comparisons (e.g., Bonferroni correction) in the group comparisons is required to minimise Type 1 error.

• Applying the Bonferroni correction formula p value ≤ α/m, where the significance level is α, and m is the number of hypotheses for multiple comparisons. In our study, we defined α as 0.05 and four groups (or hypothesis) comparisons were conducted. Applying the Bonferroni correction, a two-tailed p value of < 0.0125 (0.05/4) was considered statistically significant. (Please see Page 10-11, Line 245-248, method)

�  Participant group characteristics could be reported in a table for greater clarity and ease of comprehension.

• In our revised manuscript, we sorted the group characteristics into six categories for clarity. The six categories were as follows: demographic characteristics (age and sex), sociodemographic status (education years and individual income), kidney function measures (including blood urea nitrogen, creatinine, eGFR, urine albumin-to-creatinine ratio), comorbid conditions (including hypertension, hyperlipidemia, diabetes), blood pressure, and serum laboratory studies (including fasting glucose, HbA1c, total cholesterol, LDL-C, HDL-C, and triglycerides). (Please see Page 13-14, in Table 1).

�  It is not appropriate to say that MMSE scores decreased between stages as the participants were not followed up longitudinally. As what has been conducted are just group comparisons, the differences should be described as performance differences between groups of patients at the different stages. The use of ‘decreasing’ is misleading in this context of reporting group comparison results. In addition, within the adjusted GLMMs, it should also be phrased similarly (e.g. lower eGFR is associated with reduced QOL). Please amend throughout.

• In our revised manuscript, we replaced the word “decrease” with “lower” to avoid misleading. Accordingly, the descriptions in the Abstract, Results, and Tables 3-4 were revised.

�  In line 205, please refrain from using terminology such as ‘thoroughly investigated’ when many cognitive domains were not assessed in this study.

• Thank you for your comment. We deleted the word “thoroughly” in the text. (Please see page 21, line 363).

�  In lines 210-211, it is not accurate to say that “patients of late CKD stages 4–5 with poorer orientation, executive function begin in the early stage of CKD (stages 3a and 3b)” as the authors did not longitudinally follow a group of patients as their CKD progressed. I believe the authors are suggesting that executive function deficits are present earlier in the illness at Stage 3, so it would be more accurate to just say that executive function deficits are evident from Stage 3 CKD.

• In our revised manuscript, we have amended the description as follows: The study results expand the previous findings[25, 39] that executive function deficits are evident earlier in the CKD illness at stage 3, and patients with late CKD stages 4–5 with poorer orientation in the older Han Chinese population. (Please see page 21-22, Line 367-373, Discussion section)

�  In line 220, increasing age and female sex cannot promote cognitive impairment, rather they can be associated with greater cognitive impairment. Please rephrase.

• We revised this description as “demographic contribution should not be a single factor to explain cognitive impairment in our participants with early stage CKD. After adjustment for age and sex in models 2–4, the GLMMs showed that lower eGFR was independently associated with cognitive impairment.” (Please see page 20, line 377-380, Discussion section)

�  In line 224, it would be better to say that clinical factors do not really explain the differences in cognitive impairment between the groups.

• Thank you for your comment. We amended this text as “clinical factors did not explain the differences in cognitive impairment among the CKD groups.” (Please see page 20, Line 380-381, Discussion section)

�  Line 230-232: It is not intuitive how the authors arrived at the conclusion that their analysis “analysis supported the association between early renal function impairment and cognitive impairment should not be the confounding effect of aging only” based on the statement preceding it. Please clarify. In addition, such a conclusion has previously been reached in the literature (Brodski et al, 2019). Relatedly, the authors should better integrate and situate their findings in relation to the existing literature.

• We revised the conclusion here to say, “our analysis supported the presence of cognitive impairment in early to moderate stages of CKD in Han Chinese older adults.”

• Compared to previous studies, our study has the following key characteristics: First, previous analysis did not clarify which is the best method for assessing eGFR in elderly and cognitively impaired adults.[24, 40] Since our enrolled population is a monoethnic Chinese population, we could manage this problem by employing the BIS equation. Our conclusion is consistent with previous studies[24-26] using the MDRD and CKD-EPI equations in different ethnic and age groups. Second, our analysis included covariates of demography, sociodemographic factors, and medical comorbidities in terms of laboratory tests. Third, we performed the analysis in both genders, unlike some studies with only men[27] and women[28, 29]. An earlier study in Taiwan[29] included only midlife women in Kinmen, a group of islands off the southeastern coast of mainland China, governed as a county in Taiwan. Fourth, our nationwide sampling should have a representative population of Han Chinese. We performed a comprehensive door-to-door survey conducted by trained interviewers and laboratory examinations. Fifth, we validated the study results using the unconventional method of partial least squares regressions with principal components to investigate the factor loadings on the response variable of eGFR. Factor loadings on orientation, calculation, and complex domains were all > 0.3, which is consistent with the analysis of GLMMs. Sixth, both cognition and quality of life were surveyed in our study. (Please see Page 23-24, Line 405-421, Discussion section)

�  Line 234-242: It is unclear how this paragraph fits within the narrative.

• We have removed this paragraph from the Discussion section. Instead, the reasons for using generalized linear mixed models (GLMMS) were added in the Methods section.

�  Regarding limitations, the authors should also discuss the limits of using the MMSE for assessing cognitive function within CKD (see Brodski et al, 2019). Also see my earlier point about premorbid conditions.

• In our revised manuscript, we added the limitation of using the MMSE to assess cognitive function and premorbid conditions. These were addressed as follows:

• Despite being the most widely used instrument in the extant literature, the MMSE is known to be affected by ceiling and floor effects in different languages and populations.[26, 41, 42] While the ceiling effect indicates that the performance of MMSE, independent of cognitive state, is favorably affected by a high level of education, the floor effect suggests that performance is adversely affected by poor education.[41] In addition, the MMSE is known to be less sensitive to mild changes in cognition, and therefore may have reduced sensitivity for early CKD stages.[26] These facts could limit the generalizability and comparability of similar studies. Some studies[43, 44] indicated that the Montreal Cognitive Assessment (MoCA) showed better utility as a tool for assessing patients with CKD. Third, we did not assess severe cardiovascular diseases or other neurological disorders in our study.

• Since the NAHSIT 2013–2016 primarily focused on healthy older adults in adults, only health comorbidities of hypertension, hyperlipidemia, and diabetes mellitus were assessed in our study. (Please see Page 24, Line 423-438, Discussion section)

�  The authors should also briefly discuss the utility of cognitive remediation to address cognitive deficits, particularly in early CKD (see Tan, E. J. et al (2019). Considering the utility of cognitive remediation therapy in chronic kidney disease. Clinical and Experimental Nephrology.) for some points. This would help better contextualise the current findings.

• Thank you for your comment. The relevant discussion of cognitive remediation for older adults with early stages has been added to the manuscript as follows: Our study confirmed that CKD with cognitive impairment (especially the domains of orientation, calculation, and complex commands) is present in the early to moderate illness stages. A non-invasive behavior intervention by cognitive remediation (CR) is proposed to help promote neuroplastic change and enhance cognitive performance in patients with CKD [45]. Different CR approaches[46] can be tailored to specific cognitive deficits in patients with CKD. However, there is a shortage of CR intervention research studies to date.[45] (Please see page 24-25, Lines 440-450, Discussion section)

�  Please review the manuscript for grammatical errors throughout.

• Thank you for your comment. We consulted an English editing service to improve readability and grammatical errors in our revised manuscript.

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21 Feb 2022

Quality of Life and Cognitive Assessment in Healthy Older Asian People with Early and Moderate Chronic Kidney Disease: the NAHSIT 2013–2016 and Validation Study

PONE-D-20-31145R1

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28 Feb 2022

PONE-D-20-31145R1

Quality of Life and Cognitive Assessment in Healthy Older Asian People with Early and Moderate Chronic Kidney Disease: the NAHSIT 2013–2016 and Validation Study

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