Association between sensory impairment and incident dementia among middle-aged and older Chinese: Findings from the CHARLS cohort study

Abstract

Background

Aging is accompanied by increase in sensory impairments (SIs), including vision impairment (VI), hearing impairment (HI), and dual sensory impairment (DSI). However, prospective evidence on this association from nationally representative cohorts in China remains limited.

Objective

To investigate the association between SIs and incident dementia among Chinese adults.

Methods

From the China Health and Retirement Longitudinal Study, 7664 dementia-free adults aged ≥45 at baseline (2011–2012) were followed up until 2018 to detect incident dementia. VI (near and distance) and HI were assessed based on self-reported vision and hearing capabilities. DSI was defined as having both VI and HI. Dementia was ascertained based on cognitive batteries, informant reports, and the Activity of Daily Living scale. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).

Results

During the follow-up, 1022 (13.34%) participants developed dementia. Overall, near/distance VI (OR: 1.75 [1.13, 2.72] / 1.93 [1.29, 2.89]) and HI (OR: 3.02 [1.30, 7.02]) were all associated with higher risk of dementia. People with DSI had a significantly higher risk of dementia compared with those without SI or with only one type of SI at baseline (OR: 2.94 [1.27, 2.95]). The associations between SIs/DSI and dementia remained significant among people aged≥60 years. However, only VI was associated with dementia among people aged<60 years. After stratification by residence, the SI-dementia associations were more pronounced among rural participants.

Conclusions

SIs are associated with a higher risk of dementia. Interventions addressing SIs should be included in dementia prevention strategies.

Keywords

Alzheimer's disease China dementia prospective study sensory impairment

Introduction

Dementia, a progressive neurodegenerative syndrome marked by deteriorating cognitive and functional capacities, represents one of the most significant global health challenges in the twenty-first century. Current estimates indicate that over 55 million individuals worldwide were living with dementia by 2023, a figure projected to triple by 2050 amid rapid population aging and extended lifespans.¹ The condition imposes immense economic burdens, with annual global costs exceeding US$1 trillion due to escalating demands for long-term care, caregiver strain, and reduced productivity.² Although pathophysiological insights have advanced, effective disease-modifying therapies for the majority of dementia cases remain limited, and clinical management is still predominantly focused on palliative care and risk reduction. Consequently, identifying modifiable risk factors for early detection has become an urgent priority, aligning with recent emphases on translational research for dementia prevention.

Sensory impairment (SI) is a common chronic condition prevalent in older adults,³ including vision impairment (VI), hearing impairment (HI), and dual sensory impairment (DSI).⁴ Accumulative evidence suggests that SI is associated with cognitive impairment^5–8 and dementia.^9–12 The latest meta-analysis suggests that IS/DSI is associated with cognitive decline⁸ and the development of dementia.^11,12 However, these findings are mainly from high-income countries, and it is not clear whether the relationship between SIs and dementia would apply to low- and middle-income countries, such as China, where lifestyle, genetic, and environmental risk profiles vary considerably. Only one cross-sectional study from China found that VI and DSI (but not HI) were associated with dementia.¹⁰ Presently, evidence for a association between SI and incident dementia among Chinese adults is limited.

To fill this gap, we examined the associations between SIs and incident dementia using data from a nationally representative cohort, the China Health and Retirement Longitudinal Study (CHARLS). In addition, considering the possible heterogeneity across age and residence (rural and urban), we also explored differences in the SIs-dementia association.

Methods

Study design and participants

Initiated in 2011, China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative longitudinal survey targeting Chinese individuals aged 45 and above.¹³ Utilizing a stratified, multi-stage sampling approach proportional to population size, the study encompasses approximately 10,000 households, comprising around 17,500 participants from 450 villages and 150 counties/districts throughout China. With data collection waves in 2011 (Wave 1), 2013, 2015, 2018, and 2020 (Wave 5), CHARLS provides a rich dataset for analyzing issues related to population aging.¹³ The CHARLS database is available for detailed reference on the official CHARLS website (http://charls.pku.edu.cn/index.htm).

Ethical approval for CHARLS has been granted by the Biomedical Ethics Review Committee of Peking University (IRB00001052 - 11015). The data utilized in this research were sourced from wave 1 and wave 4 of the CHARLS.

For this analysis, exclusions were made for the following reasons: 1905 due to missing data on visual/hearing impairment, cognitive function, or age; 557 with brain diseases linked to cognitive impairment (dementia, brain atrophy, Parkinson's disease, brain damage, or mental retardation); 739 suspected of dementia at baseline; 2434 lost to follow-up by Wave 4 (2018); and 5048 with incomplete cognitive assessment data required for dementia classification in Wave 4. This yielded a final sample of 7664 participants. See Figure 1 for details.

Figure 1.

Flowchart of the study population.

Data collection

Data collection for this study was conducted through the CHARLS survey, which included comprehensive in-home assessments and standardized questionnaires administered by trained interviewers.¹³ The survey gathered detailed information on demographics (age, gender, marital status, place of residence, and educational attainment), lifestyle factors (smoking habits, alcohol consumption, and social activity engagement), health status (self-reported medical history, medication use, clinical measurements, and anthropometric measurements), and cognitive function. Blood samples were collected by medically trained personnel to measure biochemical indicators. Detailed data collection methods were provided in the Supplemental Material.

Assessment of sensory impairment

In CHARLS, participants were asked to rate their near/distance vision and hearing abilities (while using glasses, contact lenses, or hearing aids if applicable) on a scale from 1 to 5, corresponding to “excellent”, “very good”, “good”, “fair”, and “poor”, respectively.¹⁴ Scores of 4 to 5 were defined as corresponding SI. VI was categorized as no/mild impairment (absence of both near and distance vision impairments or presence of either near or distance vision impairment) and severe impairment (presence of both near and distance vision impairments or blindness). Sensory impairment was defined as no/mild impairment (no impairment or only one type of vision or hearing impairment) and DSI (both vision and hearing impairments).¹⁴

Assessment of dementia

The identification of dementia was based on a multifaceted method that combines objective cognitive function batteries, information from informants regarding cognitive status, and assessments of functional status, following the guidelines from the English Longitudinal Study of Ageing (ELSA) —an approach with established acceptable sensitivity and specificity (sensitivity 0.58, specificity 0.98) for population-based screening.^15–17 Specifically, cognitive function was measured using standardized tests from Harmonized Cognitive Assessment Protocol (HCAP) (evaluating concentration, episodic memory, executive function, and animal naming task), informant reports were collected via the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), and functional status was evaluated using the Activity of Daily Living (ADL) scale. This comprehensive assessment method is suitable for use in dementia screening tools designed for large populations, including those in community, primary care, and secondary care settings. The suspected dementia cases at baseline were defined as individuals who scored in the lowest 5% of the population on the global score of the three core cognitive tests (attention, episodic memory, and executive function). More details can be found in the Supplemental Methods. However, the above three elements of dementia definition were only complete in Wave 4; therefore, the definition of dementia was only feasible in Wave 4.

Statistical analyses

Baseline characteristics of the study population by dementia status were analyzed by chi-square tests for categorical variables and one-way analysis of variance for continuous variables. Continuous variables were presented as means and standard deviations. Categorical variables were expressed in terms of frequencies and percentages. p-values <0.05 were considered statistically significant. All statistical analyses were performed using Stata SE 16.0 for Windows (Stata Corp, College Station, TX).

Logistic regression models were employed to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the association between each SIs (near-vision, distance-vision, vision, hearing, and dual-sensory impairment) and dementia. The basic-adjusted models were adjusted for age, sex, and education. The full-adjusted models further accounted for marital status, residence, body mass index, smoking, alcohol consumption, social activity, diabetes, hypertension, cardiovascular disease (CVD), dyslipidemia, and cognitive function at baseline. Stratified analyses were conducted to examine the association between SIs and dementia by age (<60 versus ≥60 years) and residence (urban vs. rural). Interaction terms for these factors with SIs were established to assess multiplicative interactions.

Conducted sensitivity analyses to verify the stability of the results: 1) multiple imputation for missing covariates (n = 7656); 2) retaining participants suspected of dementia at baseline (n = 8035). Missing covariates (exposure and outcome variables excluded) were multiply imputed via chained equations to create 10 imputed datasets, with estimates pooled across datasets using Rubin's rules.

Results

Characteristics of the study population

Table 1 presents the baseline characteristics of the study population. Compared to those with dementia, participants without dementia tended to be younger, more likely to be male, married, urban residents, highly-educated, and less likely to be underweight. Participants without dementia were more likely to smoke, drink alcohol, and engage in social activities, and they had lower rates of hypertension and diabetes but similar rates of CVD and dyslipidemia. Additionally, individuals with dementia at Wave 4 were more likely to have SIs at baseline. To further illustrate the baseline differences between the analytical and excluded samples, we present the relevant characteristics in Supplemental Table 1. The excluded participants appeared younger, had healthier lifestyles, and slightly lower rates of comorbidities.

Table 1.

Characteristics of the study population by dementia (N = 7664).

Characteristics	Dementia-free(n = 6642)	Dementia(n = 1022)
Age, y	61.62 ± 6.77	65.20 ± 7.80
Female	3311 (49.88)	556 (54.40)
Married	5844 (87.99)	849 (83.07)
Rural	4103 (61.77)	743 (72.70)
Education
No formal education	1859 (28.00)	398 (39.02)
Middle school and below	2924 (44.04)	467 (45.78)
High school and above	1857 (27.97)	155 (15.20)
BMI, kg/m²
Underweight	375 (6.47)	79 (9.10)
Normal weight	3181 (54.89)	445 (51.27)
Overweight	1639 (28.28)	232 (26.73)
Obesity	600 (10.35)	112 (12.90)
Smoking
Never	3888 (58.54)	606 (59.30)
Former	594 (8.94)	112 (10.96)
Current	2160 (32.52)	304 (29.75)
Alcohol drinking
Non-drinker	4398 (66.21)	734 (71.82)
Drinker	2244 (33.79)	288 (28.18)
Social activity
Inactive	3346 (50.40)	618 (60.47)
Active	3293 (49.60)	404 (39.53)
Hypertension	2024 (40.99)	401 (50.25)
Diabetes	803 (16.26)	183 (22.93)
CVD	657 (11.94)	166 (21.07)
Dyslipidemia	2427 (36.98)	383 (37.96)
Near vision impairment	4527 (68.55)	758 (74.83)
Distance vision impairment	4110 (71.70)	780 (83.51)
Vision impairment	5279 (80.60)	880 (87.04)
Hearing impairment	3686 (55.51)	719 (70.42)
Sensory impairment
No/mild	3240 (49.29)	345 (34.06)
Dual sensory impairment	3333 (50.71)	668 (65.94)

Values are mean ± standard deviation or n (%).

BMI: body mass index; CVD: cardiovascular disease.

Missing data: 4 for gender; 4 for education; 1001 for BMI; 3 for social activity; 1928 for diabetes; 1928 for hypertension; 1 for CVD; and 1 for dyslipidemia.

Association between SIs and dementia

A total of 1022 (13.34%) cases of dementia were identified in wave 4. The association between SI and dementia was generally significant (Table 2). After controlling for a range of covariates, near VI was associated with a 26% higher risk of dementia (OR = 1.26, 95% CI: 1.01, 1.57), distance VI with a 71% higher risk (OR = 1.71, 95% CI: 1.31, 2.25), VI with a 58% higher risk (OR = 1.58, 95% CI: 1.18, 2.12), HI with a 53% higher risk (OR = 1.53, the 95% CI: 1.24, 1.87), and DSI was associated with a 53% increased risk of dementia (OR = 1.53, 95% CI: 1.25, 1.86).

Table 2.

Association between sensory impairments (SIs) and dementia.

SIs	No. of participants	No. of cases	Proportion (%)	Model 1		Model 2
SIs	No. of participants	No. of cases	Proportion (%)	OR (95% CI)^a	p	OR (95% CI)^b	p
Near vision impairment	7617	1013	13.30
Absence	2332	255	10.93	Reference (1.00)	—	Reference (1.00)	—
Presence	5285	758	14.34	1.35 (1.16, 1.57)	<0.001	1.26 (1.01, 1.57)	0.035
Distance vision impairment	7619	1013	13.30
Absence	1776	154	8.67	Reference (1.00)	—	Reference (1.00)	—
Presence	4890	780	15.95	1.81 (1.50, 2.18)	<0.001	1.71 (1.31, 2.25)	<0.001
Vision impairment	7663	1022	13.34
Absence	1402	131	9.34	Reference (1.00)	—	Reference (1.00)	—
Presence	6159	880	14.29	1.53 (1.26, 1.87)	0.008	1.58 (1.18, 2.12)	0.002
Hearing impairment	7661	1021	13.33
Absence	3256	302	9.28	Reference (1.00)	—	Reference (1.00)	—
Presence	4405	719	16.32	1.72 (1.49, 1.99)	<0.001	1.53 (1.24, 1.87)	<0.001
Dual sensory impairment	7664	1022	13.34
Absence	3585	345	9.62	Reference (1.00)	—	Reference (1.00)	—
Presence	4001	668	16.70	1.72 (1.49, 1.98)	<0.001	1.53 (1.25, 1.86)	<0.001

Adjusted for age, sex, and education.

Adjusted for age, sex, education, marital status, residence, body mass index, smoking, alcohol drinking, social activity, diabetes, hypertension, cardiovascular disease, dyslipidemia, and cognitive function at baseline.

OR: odds ratio; CI: confidence interval; DSI: dual sensory impairment

Age-specific associations

After stratification by age (Figure 2 and Supplemental Table 2), for participants aged <60 years, the fully adjusted model shows that distance VI was associated with a 64% higher risk (OR = 1.64, 95% CI: 1.01, 2.67); HI, a 60% higher risk (OR = 1.60, 95% CI: 1.11, 2.32); and DSI, a 1.55-fold higher risk (OR = 1.55, 95% CI: 1.09, 2.21) of dementia. For participants aged ≥60 years, near VI was associated with a 30% higher risk (OR = 1.30, 95% CI: 1.00, 1.68); distance VI, a 74% higher risk (OR = 1.74, 95% CI: 1.25, 2.41); VI, a 67% higher risk (OR = 1.67, 95% CI: 1.17, 2.37); HI, an 50% higher risk (OR = 1.50, 95% CI: 1.17, 1.93); and DSI, a 53% higher risk (OR = 1.53, 95% CI: 1.20, 1.94) of dementia. After incorporating the interaction term between SIs and age into the model, their multiplicative interactions on dementia were not significant (p > 0.05).

Figure 2.

Association between sensory impairment and dementia: stratified by age of 60.

Role of residence

After stratification by residence (Figure 3 and Supplemental Table 3), among rural participants, the fully adjusted model shows that distance VI was associated with a 60% higher risk (OR = 1.60, 95% CI: 1.18, 2.17); VI, a 52% higher risk (OR = 1.52, 95% CI: 1.09, 2.11); HI, a 46% higher risk (OR = 1.46, 95% CI: 1.16, 1.85); and DSI, a 38% higher risk (OR = 1.38, 95% CI: 1.10, 1.72) of dementia among rural participants. Among urban participants the OR (95% CI) of dementia was 1.69 (1.01, 2.80) for near VI, 2.10 (1.16, 3.81) for distance VI, 1.76 (1.13, 2.73) for HI, and 2.12 (1.38, 3.28) for DSI, respectively. The multiplicative interactions of SIs and residence were not significant on dementia risk.

Figure 3.

Association between sensory impairment and dementia: stratified by residence.

Sensitivity analysis

Similar results were observed (Supplemental Tables 4 and 5) when we repeated the analyses after 1) multiple imputation for missing covariates and 2) including those regarded as suspected dementia at baseline.

Discussion

This prospective cohort study, utilizing data from a nationally representative sample of Chinese adults, provides strong evidence that SIs, including VI, HI, and DSI, are associated with a higher risk of developing dementia. Notably, this association was more pronounced among those aged ≥60 years and living in rural areas. These findings strengthen our understanding of SIs as a practical indicator for dementia risk stratification in Chinese adults.

Although meta-analyses have confirmed SIs as a risk factor for dementia in high-income countries,^11,12 our study provides important evidence from China, a middle-income country with unique genetic and environmental characteristics. Notably, we found that both VI and HI predicted dementia, which contrasts with the only previous cross-sectional study in China (Luo et al., 2018), which reported only the correlation between VI and DSI but not HI.¹⁰ This discrepancy may reflect differences in methodology: Luo et al. used a clinical dementia diagnosis,¹⁰ whereas our population-based screening methodology captured cases with milder conditions. Importantly, our prospective design strengthens causal inference as sensory impairments were assessed at baseline, prior to the identification of incident dementia during follow-up. The strong association with DSI (OR = 2.94 for those aged≥60 years) is consistent with the positive association reported in global studies.¹¹ The elevated risk within our Chinese cohort is notable and may reflect the influence of specific population characteristics (relative risk in Western cohorts: 1.50–1.89),^18,19 such as genetic background or healthcare system factors.

In age-stratified analyses, various types of SI showed significant associations with dementia risk in both the <60 and ≥60-year-old groups. However, the formal tests for multiplicative interaction between SIs and age were not statistically significant. The observed variation in point estimates across age strata, such as the stronger association for HI in <60 years adults, must therefore be interpreted with caution. This may reflect the neurodevelopmental resilience of younger brains, where HI compensation (e.g., neural reorganization) is more effective.²⁰ After age 60, cumulative sensory deprivation may accelerate neurodegeneration through a reduction in cognitive reserve.²¹ These patterns may suggest potential differences in how sensory deficits contribute to dementia risk across the lifespan, but they could also be influenced by differing statistical power between the subgroups or other confounding factors. Future studies with larger samples and precise onset data are needed to conclusively determine whether age modifies these associations.

Rural-urban differences are also noteworthy, even though there was no statistically significant interaction effect. The stronger association between SI and dementia in rural participants may stem from inequalities in health care in rural China. Untimely and poor-quality interventions for SIs among those living in rural areas result in more severe health outcomes. In addition, sensory deficits may restrict social interaction, which is a well-known risk factor for dementia²²—and this effect is likely amplified in rural settings. According to our study data, the baseline level of active social engagement in rural areas (45.4%) is lower than that in urban areas (51.9%). Sensory impairments, when compounded with pre-existing limitations in social network diversity and resource availability,²³ may create a dual burden—significantly accelerating cognitive decline among rural older adults by intensifying social isolation and reducing cognitive stimulation.²⁴

There may be three interrelated mechanisms that explain our findings. First, there may be a common etiology for SI and dementia, such that vascular dysfunction may damage both the sensory organs and the brain. Amyloid-β deposition in the auditory cortex is exacerbated by amyloid-β deposition in the auditory cortex, which subsequently spreads to memory regions.²⁵ Second, compensation for sensory deficits diverts neural resources from higher-order cognition, and this compensatory mechanism accelerates cognition-related neurodegeneration.^26,27 Third, sensory deprivation may induce brain atrophy, as evidenced by the fact that reduced afferent signaling (especially in DSI) may trigger synaptic loss in regions of cross-modal integration²⁸ thereby accelerating the progression of cognitive deficits.

Several limitations must be acknowledged. First, residual confounding by unmeasured variables (e.g., genetic risk, dietary patterns) may persist despite multiple adjustments. Second, some participants with SIs may be unable to access the survey, potentially introducing selection bias. In addition, the use of self-reported measures for SI, while necessary for a large-scale population study, is subject to potential misclassification. This non-differential misclassification likely attenuates the observed effect sizes, suggesting that the true associations may be stronger than those reported here. Third, the determination of dementia relies on a cognitive battery rather than a clinical diagnosis, which may introduce misclassification bias. While the dementia classification algorithm has been validated in a Western cohort (ELSA), its performance characteristics (sensitivity = 0.58, specificity = 0.98) may not be directly transferable to the Chinese population due to differences in culture, education, and healthcare context. This potential misclassification is likely non-differential and would bias our results toward the null. Furthermore, due to the design of the cognitive assessment in CHARLS, where the full dementia ascertainment protocol was implemented at a specific follow-up wave, we were unable to precisely determine the time of dementia onset. This prevented a time-to-event analysis, which could provide further insights into the progression of risk. Fourth, although we excluded participants with the poorest cognitive function at baseline, some individuals with undiagnosed pre-clinical dementia might have been included in the analytical sample. This could lead to potential reverse causation, where underlying neurodegeneration contributes to both SI and subsequent clinical dementia. Therefore, the observed associations should be interpreted with this caution in mind. Fifth, to ensure a complete dementia evaluation, we included only participants who completed the 4th wave with complete HCAP data, inevitably resulting in a high proportion of missing cases. As participants lost to follow-up were generally younger and had healthier profiles at baseline, selective attrition may have introduced bias if leaving the study was associated with both SI and dementia. This could potentially result in an underestimation of the true association between SI and dementia. Finally, the nature of observational designs precludes causal inferences; that is, whether interventions to improve sensory directly reduce dementia risk remains untested.

Conclusions

In conclusion, this study demonstrates that SIs, including VI, HI, and DSI, are strong predictors of higher dementia risk in Chinese adults, especially among older adults and people living in rural. These findings highlight that self-reported SIs represent a simple and practical tool that could be feasibly integrated into initial dementia risk stratification protocols in community and primary care settings across China.

Supplemental Material

sj-docx-1-alr-10.1177_25424823251415174 - Supplemental material for Association between sensory impairment and incident dementia among middle-aged and older Chinese: Findings from the CHARLS cohort study

Supplemental material, sj-docx-1-alr-10.1177_25424823251415174 for Association between sensory impairment and incident dementia among middle-aged and older Chinese: Findings from the CHARLS cohort study by Qifa Zhang and Chaofeng Fan in Journal of Alzheimer's Disease Reports

Footnotes

Acknowledgements

We thank the China Health and Retirement Longitudinal Study team for providing data and training in using the datasets. We thank the students who participated in the survey for their cooperation. We thank all volunteers and staff involved in this research.

ORCID iD

Chaofeng Fan

Ethical considerations

Ethics approval for CHARLS was obtained from the Biomedical Ethics Review Committee of Peking University (IRB00001052-11015). The protocol was in accordance with the Declaration of Helsinki.

Consent to participate

All participants provided signed informed consent.

Consent for publication

Not applicable

Author contribution(s)

Qifa Zhang: Formal analysis; Methodology; Validation; Visualization; Writing – original draft.

Chaofeng Fan: Conceptualization; Data curation; Project administration; Software; Supervision; Writing – review & editing.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The data of this study can be obtained on the official website of CHARLS ().

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

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