Prevalence,Incidence,and Progression of Cognitive Impairment,No Dementia Among Rural-Dwelling Chinese Older Adults

Abstract

Background:

Few studies have examined occurrence and progression of cognitive impairment, no dementia (CIND) in rural China.

Objective:

To determine the prevalence and incidence of CIND in rural-dwelling Chinese older adults, and to examine risk and protective factors associated with progression to CIND and dementia.

Methods:

This population-based study included 2,781 dementia-free participants (age≥65 years) who were examined at baseline (2014) and followed in 2018. Demographic, epidemiological, clinical, and neuropsychological data were collected following a structured questionnaire. We defined CIND according to subjective cognitive complaints and the age- and education-specific Mini-Mental State Examination (MMSE) score. Data were analyzed with the multinomial logistic regression models.

Results:

The overall prevalence of CIND was 10.54% and the incidence was 28.26 per 1,000 person-years. CIND at baseline was associated with the multi-adjusted odds ratio (OR) of 2.06 (95% confidence interval = 1.23–3.47) for incident dementia. Multinomial logistic regression analysis suggested that compared with no CIND, the multi-adjusted OR of incident CIND was 2.21 (1.51–3.23) for women and 0.62 (0.38–0.99) for high social support, whereas the multi-adjusted OR of incident dementia was 1.14 (1.09–1.18) for older age, 0.29 (0.16–0.53) for high education, and 2.91 (1.47–5.74) for having a stroke history.

Conclusion:

CIND affects over one-tenth of older adults living in rural communities of western Shandong province. People with CIND are twice as likely to progress to dementia as people without CIND. Female sex, low education, stroke history, and low social support are associated with an increased risk of progression from normal cognition to CIND or dementia.

Keywords

Cognitive impairments incidence population-based study prevalence risk factors rural

INTRODUCTION

Cognitive impairment, no dementia (CIND) was proposed in the Canadian Study of Health and Aging in 1997 [1]. Similar to mild cognitive impairment, CIND is also considered as an intermediate state between normal cognitive aging and dementia, but with a broader scope and simpler definition. Population-based follow-up studies suggested that people with CIND might be at a substantial risk for cognitive decline and progression to dementia [2, 3]. Thus, exploring risk and protective factors that contribute to progression from normal cognitive function to CIND and dementia is crucial for the development of intervention strategies to slow cognitive decline or delay dementia onset.

Previous studies have shown substantial variations in prevalence and incidence of CIND due to the heterogeneity of demographics of study population and neurocognitive tests and operational criteria used to define CIND. A systematic review estimated that the prevalence of CIND ranged from ∼5% to ∼36% [4]. In addition, population-based follow-up studies of older adults showed that the incidence of CIND varied from 33.8 to 223 per 1,000 person-years [5 –10]. Apart from older age, low educational attainment and stroke were frequently reported to be associated with incident CIND [5 , 9]. The majority of the previous epidemiological studies of CIND have been carried out among urban populations in high-income countries [11], where people have relatively high education or high socioeconomic position. We have identified two population-based studies in China that investigated the prevalence of CIND among rural and urban elderly populations [12, 13]. However, no population-based cohort study has examined the incidence of CIND and the risk and protective factors for the progression from normal cognition to CIND and dementia.

In this prospective cohort study of rural-dwelling older adults in western Shandong province, we aimed to: 1) investigate the prevalence and incidence of CIND and 2) examine sociodemographic, lifestyle, and clinical factors associated with progression from normal cognition to CIND and dementia.

METHODS

Study participants

This study is part of the Shandong Yanggu Study of Aging and Dementia (SYS-AD), a population-based cohort study that targeted rural residents aged≥65 years in Yanlou town, Yanggu county, western Shandong province, as previously reported [14]. In brief, at baseline (August-December 2014), 3,189 participants (59.5% of 5,360 eligible persons) were examined for SYS-AD. Out of these, 495 were excluded due to prevalent dementia (n = 199) or insufficient information for determining the dementia status (n = 209). Thus, the analytical sample for the prevalence of CIND included 2,781 participants who were free of dementia at baseline. Of these, 293 subjects were defined as having CIND in the baseline survey, 182 died before follow-up examination in 2018, 411 lost contact or refused to attend the follow-up examination, and 52 had incomplete follow-up data, leaving 1,843 participants for the analysis involving the progression from normal cognitive function to CIND and dementia. Figure 1 shows the flowchart of study participants. Compared with people who were lost to follow-up in 2018 (n = 645), those who undertook the follow-up examination (n = 1,843) were younger (mean age, 70.07 versus 74.03 years; p < 0.001), more educated (middle school or above, 16.22% versus 15.19%; p < 0.001), and more likely to be women (57.95% versus 47.29%; p < 0.001) and farmers (90.33% versus 85.21%; p < 0.001). In addition, there were no significant differences between the 3,189 participants (age≥65 years) who were recruited in the 2014 survey (SYS-AD) and the 5,246 participants (age≥65 years) who were recruited in the 2018 wave of survey (MIND-China) in the mean age (71.79 versus 71.74 years, p = 0.497) and sex distribution (females 57.54% versus 57.17%, p = 0.736). However, participants in the 2014 survey were more likely to be illiterate than those in the 2018 survey (44.12% versus 40.68%, p = 0.007), which was expected.

Fig. 1

Flowchart of study participants, 2014 to 2018. CIND, cognitive impairment, no dementia.

All waves of data collection for the SYS-AD study were approved by the Ethics Committee on Human Experimentation at Shandong Provincial Hospital affiliated to Shandong University in Jinan, Shandong, China. Written informed consents were obtained from all participants, or if the participants were not able to give the consent due to severe cognitive impairment, from the informants.

Data collection

At baseline, data were collected by trained staff through face-to-face interviews, clinical examinations, neuropsychological testing, and laboratory tests. Data on sociodemographic features (e.g., age, sex, education, and occupation), lifestyle habits (e.g., cigarette smoking and alcohol drinking), use of medications (e.g., antihypertensive, lipids-lowering, and blood glucose-lowering drugs), and medical history were collected. Arterial blood pressure was measured on the right upper arm in the sitting position after a 5-min rest using an electronic blood pressure monitor (Omron HEM-7127J; Omron Corporation, Kyoto, Japan). After an overnight fast, blood samples were taken, and fasting blood glucose and lipids were measured at the clinical laboratory of Yanlou Town Hospital. Hypertension was defined as systolic pressure≥140 mmHg or diastolic pressure≥90 mmHg or current use of any antihypertensive drugs. Diabetes was defined according to fasting blood glucose≥7.0 mmol/L or self-reported physician diagnosis of diabetes or current use of antidiabetic agents. Hyperlipidemia was defined as total serum cholesterol≥6.22 mmol/L or triglyceride≥2.27 mmol/L, or low-density lipoprotein cholesterol≥4.14 mmol/L, or high-density lipoprotein cholesterol < 1.04 mmol/L, or current use of lipid-lowering agents. Ischemic heart disease was identified according to self-report history of myocardial infarction, angina pectoris, coronary intervention, or pathological Q waves on electrocardiogram. History of clinical stroke was ascertained according to self-reported history of stroke or neurological examination by a neurologist. Social support (e.g., living alone or with family members and contact with or support from family members, neighbors or colleagues) was assessed using the Social Support Rating Scale (SSRS) [15]. We used the Pittsburgh Sleep Quality Index (PSQI) [16] to assess sleep quality and patterns. We used the screening tests of the Mini-Mental State Examination (MMSE) [17] and the self-rated Ascertain Dementia 8-item Questionnaire (AD8) [18] to assess global cognitive function.

Follow-up assessments

The follow-up survey was conducted in March-September 2018, which is part of the baseline assessment of the Multimodal Interventions to Delay Dementia and Disability in Rural China (MIND-China) [19]. At this wave of assessment, we collected data on demographics, lifestyles, cardiometabolic risk factors, clinical conditions, and blood biochemicals. Global cognitive function was assessed using the MMSE and self-rated AD8 tests in the same way as used in the baseline examination of the SYS-AD study.

Defining criteria of CIND and diagnosis of dementia

At both baseline (2014) and follow-up (2018) examinations, dementia was diagnosed following the criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) [20]. The diagnosis of dementia was made by a panel of neurologists specialized in dementia diagnosis and care following a 3-step procedure in both baseline and follow-up examinations. In brief, the trained medical staff performed the initial first face-to-face interviews, clinical examinations, and assessments of cognitive and physical functioning, and recorded all information following structured questionnaires. Then, neurologists reviewed all the records from the initial assessments to screen people who were suspected to have dementia or who had insufficient information for a judgement of dementia status for further evaluations. Finally, senior neurologists conducted the second interview with persons who were suspected to have dementia and their caregivers, reassessed subjects’ medical history, cognitive status, daily living ability, and neuroimaging data (if available), and reached a final diagnosis of dementia following the DSM-IV criteria [20]. Among participants who were free of dementia, CIND was defined according to the following criteria [21]: 1) subjective cognitive complaints, defined as self-rated AD8 score≥2; and 2) objective impairment in global cognition, defined as the MMSE score≥1 standard deviation (SD) below the age- and education-specific mean MMSE scores.

Statistical analysis

Continuous variables were described using mean (SD) and categorical variables as frequency (%). We used the Student’s t-test for continuous variables and the χ² test for categorical variables. The prevalence of CIND was calculated in the total dementia-free population and after stratification by age and sex. The incidence rates of CIND were estimated according to person-years of follow-up (per 1,000 person-years) in the total sample and by age groups and sex. The follow-up time was estimated from the date of baseline examinations in 2014 to the date of 2018 follow-up assessments. Multinomial logistic regression models, controlling for age, sex, and education, were used to examine various factors at baseline associated with the progression from normal cognitive function to incident CIND and dementia determined at follow-up. SAS 9.4 software (SAS Institute Inc., 2013, Cary, NC, USA) was used for all statistical analyses. Two-tailed p≤0.05 was considered to be statistically significant.

RESULTS

Baseline characteristics of study participants

At baseline, the mean age of the 2,781 participants was 71.20 (SD, 5.42) years, 56.71% were women, and 40.85% were illiterate (Table 1). Compared to those without CIND, participants with CIND were older, less educated, and less likely to smoke and drink alcohol, and more likely to be female and to have a stroke history, a lower SSRS score, and a higher PSQI score (p < 0.05). The two groups did not differ significantly in the distribution of farmers, hypertension, diabetes mellitus, hyperlipidemia, and ischemic heart disease (Table 1).

Table 1

Baseline characteristics of study participants in the total sample and by cognitive impairment, no dementia (n = 2,781)

Characteristics ^*	Total sample (n = 2,781)	Cognitive impairment, no dementia
		No (n = 2,488)	Yes (n = 293)	p
Age (y), mean (SD)	71.20 (5.42)	71.09 (5.34)	72.15 (6.01)	0.002
Age group (y), n (%)				0.010
65–69	1,336 (48.04)	1,208 (48.55)	128 (43.69)
70–74	777 (27.94)	705 (28.34)	72 (24.57)
75–79	403 (14.49)	350 (14.07)	53 (18.09)
≥80	265 (9.53)	225 (9.04)	40 (13.65)
Female sex, n (%)	1,577 (56.71)	1,373 (55.18)	204 (69.62)	< 0.001
Educational level, n (%)
Illiterate	1,136 (40.85)	992 (39.87)	144 (49.15)	0.007
Primary school	1,213 (43.62)	1,099 (44.17)	114 (38.91)
Middle school or above	432 (15.53)	397 (15.96)	35 (11.95)
Occupation, n (%)				0.100
Farmer	2,480 (89.34)	2,210 (89.01)	270 (92.15)
Non-farmers	296 (10.66)	273 (10.99)	23 (7.85)
Lifestyle factors
Ever smoking, n (%)	1,020 (36.72)	937 (37.71)	83 (28.33)	0.002
Alcohol consumption, n (%)	993 (35.75)	912 (36.70)	81 (27.65)	0.002
Physical inactivity, n (%)	1,132 (42.02)	1,005 (41.81)	127 (43.79)	0.517
Cardiometabolic factors
Obesity, n (%)	499 (20.21)	451 (20.41)	48 (18.53)	0.477
Hypertension, n (%)	1,990 (71.74)	1,771 (71.33)	219 (75.26)	0.159
Diabetes mellitus, n (%)	368 (13.25)	324 (13.04)	44 (15.02)	0.345
Hyperlipidemia, n (%)	725 (26.12)	650 (26.18)	75 (25.60)	0.831
Ischemic heart disease, n (%)	529 (19.08)	472 (19.02)	57 (19.52)	0.838
Stroke, n (%)	275 (9.92)	230 (9.27)	45 (15.41)	< 0.001
SSRS score, mean (SD)	24.55 (4.06)	24.68 (4.03)	23.50 (4.16)	< 0.001
PSQI score, mean (SD)	5.70 (3.94)	5.58 (3.88)	6.76 (4.26)	< 0.001
MMSE score, mean (SD)	21.82 (5.29)	22.74 (4.61)	14.00 (4.10)	< 0.001
AD8 score, mean (SD)	1.73 (1.63)	1.49 (1.48)	3.72 (1.48)	< 0.001

CIND, cognitive impairment, no dementia; SSRS, Social Support Rating Scale; PSQI, Pittsburgh Sleep Quality Index; MMSE, Mini-Mental State Examination; AD8, Ascertain Dementia 8-item Questionnaire. ^*The number of subjects with missing value was 5 in occupation, 3 in smoking, 3 in alcohol consumption, 87 in physical exercise, 312 in obesity, 7 in hypertension, 3 in diabetes, 5 in hyperlipidemia, 8 in coronary heart disease, 8 in stroke, 64 in SSRS, and 264 in PSQI.

Prevalence of CIND

Of the 2,781 participants, the overall prevalence of CIND was 10.54% (95% CI 9.39%–11.68%), with the prevalence being much higher in women (12.94%; 95% CI 11.28%–14.59%) than in men (7.39%; 95% CI 5.91%–8.87%). In addition, the proportion of either having subjective cognitive complaints alone or having objective cognitive impairment alone was 35.85% and 4.71%, respectively. Overall, the prevalence of CIND increased with age, from 9.58% in people aged 65–69 years to 15.09% in those aged 80-years and above, and the prevalence was higher in women than men across all age groups (Fig. 2A). After adjusting for age and education, women had an 85% increased likelihood of having CIND than men (OR = 1.85; 95% CI 1.38–2.48).

Fig. 2

A) The age- and sex-specific prevalence (per 100 population) of cognitive impairment, no dementia. B) The age- and sex-specific incidence (per 1,000 person-years) of cognitive impairment, no dementia.

Incidence of CIND

Of the 1,843 participants who were free of CIND and dementia at baseline (2014) and who completed the 2018 follow-up assessments, 84 (4.56%) developed dementia and 189 (10.26%) progressed to CIND during an average of 3.80 years (SD, 0.15) of follow-up. The overall incidence rate (per 1,000 person-years) of CIND was 28.26 (95% CI 24.23–32.29), with the incidence rate being higher in women (37.13; 95% CI 31.02–43.24) than in men (16.41; 95% CI 11.72–21.10) (p < 0.001). The overall incidence of CIND was relatively stable in the groups of people aged 65–69 and 70–74 years, but slightly increased thereafter, driven primarily by the increasing incidence in women (Fig. 2B). The incidence rate was higher in women than in men across all age groups.

Association of baseline CIND with incident dementia

Out of the 2,049 participants who were free of dementia at baseline (2014) and who undertook the 2018 follow-up assessment, 206 were defined to have CIND at baseline, and 106 developed incident dementia during an average of 3.80 years (SD, 0.15) of follow-up. Controlling for age, sex, and education, baseline CIND was significantly associated with an over two-fold increased risk of dementia (adjusted OR = 2.06; 95% CI 1.23–3.47).

Risk and protective factors for incident CIND and dementia

Multinomial logistic regression analysis suggested that female sex was associated with an increased risk of progression from normal cognitive function to CIND (P < 0.05), whereas older age, low education, and a history of stroke were associated with an increased risk of progression from normal cognitive function to dementia (p < 0.05) (Table 2). In addition, a higher SSRS score was associated with a reduced risk of CIND. None of any other examined factors was significantly associated with either CIND or dementia (Table 2).

Table 2

Risk and protective factors associated with conversion from normal cognitive function to cognitive impairment, no dementia and dementia: multinomial logistic regression analysis (n = 1,843)

Characteristics ^a	No. of subjects	CIND (n = 189)		Dementia (n = 84)
		No. of cases	Odds ratio (95% CI)^b	No. of cases	Odds ratio (95% CI)^b
Age (y)			1.00 (0.96–1.04)		1.14 (1.09–1.18)^*
Sex
Male	775	47	1.00 (Reference)	23	1.00 (Reference)
Female	1,068	142	2.21 (1.51–3.23)^*	61	1.12 (0.62–2.02)
Educational level
Illiterate	672	89	1.00 (Reference)	60	1.00 (Reference)
Primary school or above	1,171	100	0.79 (0.56–1.11)	24	0.29 (0.16–0.53)^*
Occupation
Non-farmers	1,663	181	1.00 (Reference)	81	1.00 (Reference)
Farmer	178	8	1.85 (0.88–3.91)	3	1.75 (0.52–5.91)
Smoking
Never	1,193	149	1.00 (Reference)	60	1.00 (Reference)
Ever	650	40	0.90 (0.49–1.65)	24	2.20 (0.91–5.31)
Alcohol consumption
Never	1,191	146	1.00 (Reference)	60	1.00 (Reference)
Ever	652	43	0.95 (0.57–1.57)	24	1.87 (0.92–3.80)
Physical exercise
Yes	1,058	108	1.00 (Reference)	54	1.00 (Reference)
No	725	76	0.98 (0.71–1.34)	25	0.68 (0.41–1.11)
Obesity (BMI≥28 kg/m²)
No	1,339	130	1.00 (Reference)	59	1.00 (Reference)
Yes	379	42	1.09 (0.75–1.58)	19	1.33 (0.76–2.31)
Hypertension
No	475	45	1.00 (Reference)	15	1.00 (Reference)
Yes	1,368	144	1.07 (0.75–1.53)	69	1.43 (0.80–2.58)
Diabetes mellitus
No	1,589	156	1.00 (Reference)	72	1.00 (Reference)
Yes	254	33	1.38 (0.92–2.08)	12	1.53 (0.79–2.96)
Hyperlipidemia
No	1,320	139	1.00 (Reference)	53	1.00 (Reference)
Yes	522	50	0.83 (0.58–1.17)	31	1.40 (0.87–2.25)
Ischemic heart disease
No	1,503	155	1.00 (Reference)	64	1.00 (Reference)
Yes	340	34	0.91 (0.61–1.35)	20	1.29 (0.75–2.21)
Stroke history
No	1,689	175	1.00 (Reference)	72	1.00 (Reference)
Yes	154	14	1.02 (0.57–1.83)	12	2.91 (1.47–5.74)^*
SSRS score
< 20	163	23	1.00 (Reference)	13	1.00 (Reference)
≥20	1,636	163	0.62 (0.38–0.99)^*	67	0.52 (0.27–1.01)
PSQI score
< 7	1,088	100	1.00 (Reference)	46	1.00 (Reference)
≥7	581	70	1.22 (0.88–1.70)	29	1.01 (0.61–1.66)

CIND, Cognitive impairment, no dementia; BMI, body mass index; SSRS, Social Support Rating Scale; PSQI, Pittsburgh Sleep Quality Index. ^aThe number of subjects with missing value was 1 in occupation, 60 in physical exercise, 125 in obesity, 1 in hyperlipidemia, 44 in SSRS, and 174 in PSQI. Dummy variables were corrected to indicate those with missing values. ^bOdds ratio and 95% confidence interval were controlled for age, sex, and education. ^*p < 0.05.

DISCUSSION

In this community-based cohort study of rural older adults in western Shandong province of China, we sought to examine the prevalence and incidence of CIND as well as potential risk and protective factors for progression from normal cognition to CIND and dementia. The main findings can be summarized as follows: 1) overall, the prevalence of CIND was 10.54% and the incidence was 28.26 per 1,000 person-years, with both prevalence and incidence being higher in women than in men; 2) older adults with CIND have an over two-fold increased risk of developing dementia during the 4 year period; and 3) older age, female sex, illiterate, low levels of social support, and a history of clinical stroke are associated with an increased risk of progression from normal cognition to CIND or dementia.

The prevalence and incidence of CIND vary substantially across studies, partly due to methodological differences such as sociodemographic features of the study populations, as well as neuropsychological tests and operational criteria and procedure used for defining CIND (e.g., cut-off for defining objective cognitive impairment). In the current study, we defined CIND by integrating objective cognitive impairment assessed with the MMSE test and subjective cognitive complaints assessed with the self-rated AD8. In a small-scale randomized controlled trial of sedentary individuals (age > 55 years) with CIND, having subjective cognitive complaints was an essential criterion in defining CIND [22]. The AD8 is sensitive to early cognitive changes and has a good discrimination between individuals with and without cognitive impairment [23 –25]. However, most of the previous studies have not included subjective cognitive complaints as the essential component for defining CIND.

We used the MMSE test (based on the age- and education-specific mean MMSE scores) to assess objective cognitive impairment, as did in most of the previous studies [12 , 26–30]. Different cut-offs of MMSE score used for defining objective cognitive impairment greatly affect the prevalence of CIND. For instance, in the population-based study of urban residents aged 60 years and older in Tianjin, China, the prevalence of CIND was 23.3% when an MMSE score cutoff of 0.5 SD below the mean was used to define objective cognitive impairment [31]. In the Faenza Community Aging Study in Italy, objective cognitive impairment was defined as the cognitive test score below 2.0 SDs of the age- and education-adjusted means of the study population, which yielded the CIND prevalence of 5.1% [26]. In the present study, we used the cutoff of≥1.0 SD below the age- and education-specific mean MMSE scores to define objective cognitive impairment in the operational criteria for CIND together with subjective cognitive complaints, which yielded a prevalence of 10.54% for CIND in people aged 65 years or older. Our result is overall comparable with the reports from the Spanish Ariadna Study of people aged≥65 years (prevalence of CIND, 14.5%; 95% CI, 12.4%–16.8%), in which the same approach for defining objective cognitive impairment (≥1.0 SD below the age- and education-specific mean MMSE scores) was used [29]. A previous study showed that CIND defined using the cutoff of≥1.0 SD below normative data was associated with a highest risk of developing dementia during the follow-up period [32]. In our study, we integrated objective global cognitive impairment with subjective cognitive complaints to define CIND, which is feasible and convenient for large-scale population-based studies.

The incidence of CIND was previously reported in a few population-based studies. The InChianti Study of people over 60 years in Italy, which used an MMSE cutoff score of≥1.0 SD below the age-specific means, showed that incidence of CIND was 66.0 per 1,000 person-years [7]. The US Aging, Demographics, and Memory Study of a national representative sample of people aged over 72 years showed that the incidence of CIND was 60.4 per 1,000 person-years when CIND was defined through clinical judgement [10]. We reported the CIND incidence of 28.26 per 1,000 person-years, which appears to be relatively lower compared to above mentioned studies, partly because having subjective cognitive complaints was part of our defining criteria for CIND. Our data did not show a strong trend of increasing prevalence and incidence of CIND with an advancing age, largely due to the fact that age was already taken into consideration when defining CIND in our study. This age-specific pattern of CIND prevalence is in a good agreement with the previous reports, in which similar approaches (e.g., age- and education-specific normative values of MMSE score) were used to define CIND [29, 33].

We found that women had higher prevalence and incidence of CIND than men overall and across all age groups, even when controlling for age and education, a sex pattern that is similar to some of the previous studies [7, 8], but not others [5, 6]. In addition, we found no association of sex with progression from normal cognition to dementia. Indeed, evidence supporting sex differences in the risk of cognitive impairment and dementia across ethnic groups are mixed [34]. The sex differences in the risk of CIND and dementia among Asian populations merit further investigation.

The lack of association between education and incident CIND was largely because educational level was part of our operational approach for defining CIND. Even though our study population had relatively low education (40.85% were illiterate), we still found that people who received education had lower risk of dementia compared with illiterate persons. High education has been consistently associated with reduced prevalence and incidence of dementia in numerous studies [35]. The cognitive reserve hypothesis has been proposed to explain the beneficial effects of educational attainment on cognitive function [36].

Clinical stroke or even silent brain infarction is a well-established risk factor for dementia, especially for vascular dementia or vascular cognitive impairment [9, 26]. Stroke and dementia share common risk factors and often co-occur [9, 37]. In the present study, a history of stroke was associated with a nearly three-fold increased risk of developing dementia, although the association with incident CIND was not evident, possibly because clinical stroke is associated with fast progression to dementia [38].

Social support has been associated with psychological well-being and cognitive function [39]. We found that a higher SSRS score was associated with a reduced risk of progression from normal cognition to CIND. This is in line with a few previous reports. For instance, data from the Chinese Longitudinal Healthy Longevity Survey showed that social support was associated a lower risk of cognitive impairment [40]. A recent report from the Portuguese prospective study found that social support network from friends may reduce the risk of cognitive impairment in older people [41]. Similarly, the Longitudinal Study of an INDEPTH community in South Africa also supported the association between less social support and lower cognitive function [42]. Lack of supportive social relationships may promote unhealthy behaviors, such as smoking, harmful alcohol use, physical inactivity, overweight or obesity, and depression [43, 44], which may partly explain the link of low levels of social support with poor cognitive health (e.g., CIND and dementia).

The major strength of our study refers to the community-based cohort study targeting rural residents. In addition, we employed a definition of CIND that integrated objective global cognitive impairment assessed using the MMSE test with coexistence of subjective cognitive complaints. Nonetheless, some limitations should be considered when interpreting our data. First, around one-fourth of our baseline participants either died during the follow-up period or were lost to follow-up, and we were not able to determine the cognitive or dementia status for deceased persons. Individuals who were lost to follow-up were older and more likely to be men and non-farmers compared with those who were included in the analytical sample. This may lead to underestimation of the true prevalence and incidence of CIND as well as their associations with risk or protective factors. Furthermore, our study participants were recruited from only one rural region in western Shandong province. Thus, cautiousness is needed when generalizing the present findings to different populations.

Conclusion

In conclusion, CIND affects over one-tenth of older adults living in rural communities of western Shandong province of China and is associated with an over 2-fold increased risk of developing dementia. Older age, female sex, illiterate, a history of clinical stroke, and low levels of social support are associated with an increased risk of progression from normal cognition to CIND or dementia. These findings help bridge the knowledge gap of epidemiological features (e.g., distributions, risk and protective factors, and prognosis) of CIND in rural populations in China.

Footnotes

ACKNOWLEDGMENTS

We would like to thank all the participants of the Shandong Yanggu Study of Aging and Dementia and the MIND-China Project as well as the staff of the Yanlou Town Hospital and Shandong Provincial Hospital who were involved in the data collection and management. The Shandong Yanggu Study of Aging and Dementia was financially supported by the Science and Technology Program for Public Wellbeing of Shandong Province, China (grant no. 2013kjhm180405). MIND-China was supported in part by grants from the National Key R&D Program of China (grant no.: 2017YFC1310100), the National Natural Science Foundation of China (grants no.: 81861138008 and 8191101618), the Academic Promotion Program of Shandong First Medical University, and the Taishan Scholar Program of Shandong Province, China. C Qiu received grants from the Swedish Research Council (VR, grants no.: 2017-00740, 2017-05819, and 2020-01574) for the Sino-Sweden Network and Research Projects, the Swedish Foundation for International Cooperation in Research and Higher Education (STINT, grant no.: CH2019-8320) for the Joint China-Sweden Mobility program, and Karolinska Institutet, Stockholm, Sweden. The funding agency had no role in the study design, data collection and analysis, writing of this manuscript, and in the decision to submit the work for publication.

Authors’ disclosures available online ().

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