Association Between Hearing Impairment and Cardiometabolic Multimorbidity Among Middle-Aged and Older Adults in China

Association Between Hearing Impairment and Cardiometabolic Multimorbidity Among Middle-Aged and Older Adults in China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Association Between Hearing Impairment and Cardiometabolic Multimorbidity Among Middle-Aged and Older Adults in China Xiao-duo Zhang, Qia-chun Zhang, Bin Deng, Zhi-jian Peng, Yin-zhi Song, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7920636/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract This study examined the association between hearing impairment (HI) and the risk of cardiometabolic multimorbidity (CMM) in middle-aged and older adults, providing evidence to support early warning and screening of high-risk CMM populations. This study analyzed data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011 to 2018. The analysis included 9,035 participants aged 45 years and older. The association between HI and the risk of CMM was investigated using multivariable Cox proportional hazards regression, Kaplan–Meier survival curves, and subgroup analyses. The results were as follows: Over a median follow-up of 7 years, 382 incident CMM cases were documented. Compared to individuals with normal hearing, those with mild HI had a 31% increased risk of CMM (Hazard Ratio [HR] = 1.31, 95% Confidence Interval [CI]: 1.04–1.64), while those with severe HI had a 56% increased risk (HR = 1.56, 95% CI: 1.16–2.10). Subgroup analyses revealed that among women, the risk of CMM was significantly elevated by 51% (HR = 1.51, 95% CI: 1.11-2.00) for mild HI and by 56% (HR = 1.56, 95% CI: 1.03–2.37) for severe HI. Among individuals aged ≥ 60 years, severe HI was associated with a 69% increased risk (HR = 1.69, 95% CI: 1.14–2.51). However, no statistically significant associations were observed in men or in the 45–60 age group ( P >0.05). Our findings suggest that HI is an independent risk factor for incident CMM in middle-aged and older adults, with the association being more pronounced in women and individuals aged 60 years or older. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Hearing impairment Cardiometabolic Multimorbidity Middle-Aged and Older Adults China Health and Retirement Longitudinal Study Cohort Study Figures Figure 1 Figure 2 1. Introduction Cardiometabolic multimorbidity (CMM) refers to the coexistence of two or more cardiometabolic diseases (CMD), such as diabetes, cardiovascular disease (CVD), and stroke 1 – 2 . With the accelerating aging of the global population, the prevalence of CMM has risen significantly, establishing it as a major public health issue that threatens the health of middle-aged and older adults 3 – 4 . Compared to individuals with a single CMD, those with CMM face substantially higher risks of all-cause mortality, recurrent cardiovascular events, and healthcare resource utilization, imposing a considerable burden on healthcare systems 5 – 6 . Therefore, identifying modifiable risk factors for CMM and developing early intervention strategies are of significant clinical importance. Hearing impairment (HI) is a highly prevalent sensory disorder in older adults and represents the third leading cause of disability globally 7 – 8 , and its incidence increases with age. Approximately 1.57 billion people globally experienced some degree of hearing loss (HL) in 2019, representing 19.3% of the world's population 9 . Among adults aged 60 years and older, the prevalence of disabling HL surpasses 25% 10 . In recent years, the association between HI and systemic chronic disorders has garnered increasing attention, particularly in the field of cardiometabolic health. Previous studies have indicated that individuals with HI have a 20% increased risk of developing CVD compared to those with normal hearing 11 , the underlying mechanisms may be associated with pathophysiological pathways such as cochlear microvascular ischemia, chronic inflammation, and oxidative stress 12 . Furthermore, a cross-sectional study revealed a significantly higher risk of CMM among individuals with dual impairment of sensory vision and hearing (odds ratio [OR] = 1.862, 95% confidence interval [CI]: 1.387–2.500) 13 . However, the independent association between HI with CMM and their dose-response relationship remain unclear. This study employs nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS) to systematically examine the association between HI and CMM, aiming to establish a scientific foundation for early prevention and screening of high-risk populations for CMM. 2. Materials and methods 2.1 Data and sample sources The data for this study were derived from the CHARLS. CHARLS is a nationally representative prospective cohort study of middle-aged and older adults (≥ 45 years) in China. Its sampling framework spans 28 provinces, 150 county-level units, and 450 village-level units, ensuring strong regional and population representativeness 14 . The study encompasses comprehensive assessments of sociodemographic characteristics (e.g., age, sex, education level), health status and functioning (e.g., history of chronic diseases, hearing function, and activities of daily living), and socioeconomic status (e.g., income, health insurance coverage). CHARLS data collection began with the baseline survey in 2011, and follow-up surveys were conducted in 2013, 2015, 2018, and 2020. The baseline survey was initiated in 2011, with follow-up surveys conducted in 2013, 2015, 2018, and 2020. The CHARLS was approved by the Biomedical Ethics Committee of Peking University (IRB00001052-11015). All participants provided written informed consent. The datasets can be accessed through the official website ( http://charls.pku.edu.cn/en/ ). This study employed data from the CHARLS spanning from 2011 to 2018 to analysis. The inclusion criteria were as follows: (1) age ≥ 45 years; (2) completion of hearing function assessment and cardiometabolic-related evaluations at baseline survey; and (3) availability of complete clinical data. The exclusion criteria were as follows: (1) age < 45 years (n = 649); (2) missing data on key covariate information (e.g., sex, marital status, education level, smoking history and alcohol use history, n = 3952); (3) incomplete data on chronic disease history (including hypertension, diabetes, heart disease, stroke, and chronic kidney disease [CKD], n = 217); (4) pre-existing CMM at baseline survey (n = 400); and (5) death or loss to follow-up during the study period (n = 3445). Ultimately, a total of 9,035 participants were included in the analysis. The detailed screening process is illustrated in Fig. 1. 2.2. Assessment of Hearing status and CMM Hearing function was evaluated with a standardized question from the CHARLS questionnaire: “Is your hearing excellent, very good, good, fair, or poor (with using hearing aid if they use)?” 15 . Hearing status was classified into three groups based on established diagnostic criteria‌ 7, 1 6 : normal hearing (self-reported “excellent,” “very good,” or “good”), mild HI (self-reported “fair”), and severe HI (self-reported “poor” or daily use of hearing aid). The presence of CMD was assessed through self-reported physician diagnosis of any of the following conditions: (1) diabetes or hyperglycemia; (2) stroke; (3) CVD (including coronary heart disease, angina, congestive heart failure, or other cardiac disorders) 17 . CMM was defined as the concurrent presence of two or more CMD during follow-up. 2.3. Assessment of Covariates The covariates included in this study encompassed demographic characteristics (including age, sex, education level, marital status), lifestyle factors (including smoking history, alcohol use history), body mass index (BMI), and medical history (including hypertension, CKD). Education level was reclassified from the original 12 categories into four levels: illiterate, primary school, junior high school, and high school or above. Marital status was categorized into married/cohabiting and other (including divorced, widowed, and unmarried). Smoking and alcohol use histories were recorded as binary variables (yes/no). BMI was calculated as weight (kg) divided by the square of height (m). Medical history of hypertension and CKD was determined based on self-reported physician diagnoses. All covariate data were obtained from standardized questionnaires and physical examination records to ensure data consistency and completeness. 2.4. Statistical Analysis Normally distributed continuous variables were expressed as mean ± standard deviation (SD) and compared using the t-test. Non-normally distributed continuous variables were expressed as median and interquartile range and compared using the Mann-Whitney U test. Categorical variables were presented as frequencies and percentages and compared between groups using Fisher’s exact test or Pearson’s chi-square test, as appropriate. The Kaplan–Meier survival curves were used to describe the cumulative incidence risk of CMM for different hearing status groups, and differences between groups were compared using the log-rank test. Cox proportional hazards regression model were used to calculate hazard ratio (HR) and 95% CI for the association between hearing status and CMM. The following three models were constructed: Model 1 was unadjusted; Model 2 was adjusted for age and sex; and Model 3 was further adjusted for smoking history, alcohol use history, education level, marital status, BMI, hypertension, and CKD based on Model 2. To verify the robustness of the results, subgroup analyses were stratified by age (45–60 years/≥60 years) and sex (male/female) to explore the heterogeneity of the association between HI and CMM across different populations. All tests were two-sided, and a P -value < 0.05 was considered statistically significant. Data analysis was performed using Zstats software (version 1.0; http://www.zstats.net ) and R (version 4.3.3). 3. Results 3.1. Baseline Characteristics of study participants A total of 9,035 participants aged 45 years or older were included in this study, including 3,944 participants (43.65%) in the normal hearing group, 3,802 participants (42.08%) in the mild HI group, and 1,289 participants (14.27%) in the severe HI group. Statistically significant differences were observed in the three groups in terms of age, BMI, smoking history, alcohol use history, marital status, education level, prevalence of hypertension and CKD (all P < 0.05). The normal hearing group was younger (57.07 ± 8.40 years), had a lower prevalence of hypertension (35.6%) and CKD (4.61%), and a higher education level (12.91% with high school or above) at baseline. In contrast, the severe HI group was older (62.30 ± 9.38 years), had a higher prevalence of hypertension (42.98%), and a lower education level (40.11% with illiterate). The baseline characteristics of study participants are depicted in Table 1 . Table 1 Baseline characteristics of study participants Characteristics Overall N = 9,035 Normal hearing N = 3,944 Mild HI N = 3,802 Severe HI N = 1,289 P -value Age (years) 58.57 ± 8.78 57.07 ± 8.40 58.86 ± 8.55 62.30 ± 9.38 < 0.05 Sex, N (%) 0.066 Male 4167 (46.12%) 1873 (47.49) 1707 (44.90) 587 (45.54) Female 4868 (53.88%) 2071 (52.51) 2095 (55.10) 702 (54.46) BMI, N (%) < 0.05 <24 kg/m² 6245 (69.12%) 2663 (67.52) 2624 (69.02) 958 (74.32) ≥ 24 kg/m² 2790 (30.88%) 1281 (32.48) 1178 (30.98) 331 (25.68) Alcohol use history, N (%) < 0.05 No 6049 (66.95%) 2575 (65.29) 2568 (67.54) 906 (70.29) Yes 2986 (33.05%) 1369 (34.71) 1234 (32.46) 383 (29.71) Smoking history, N (%) < 0.05 No 6253 (69.21%) 2671 (67.72) 2670 (70.23) 912 (70.75) Yes 2782 (30.79%) 1273 (32.28) 1132 (29.77) 377 (29.25) Marital status, N (%) < 0.05 Other 947 (10.48%) 380 (9.63) 380 (9.99) 187 (14.51) Married/cohabiting 8088 (89.52%) 3564 (90.37) 3422 (90.01) 1102 (85.49) Educational level, N (%) < 0.05 Illiterate 2535 (28.06%) 993 (25.18) 1025 (26.96) 517 (40.11) Primary school 3743 (41.43%) 1528 (38.74) 1681 (44.21) 534 (41.43) Junior high school 1850 (20.48%) 914 (23.17) 773 (20.33) 163 (12.65) High school or above 907 (10.04%) 509 (12.91) 323 (8.50) 75 (5.82) CKD, N (%) < 0.05 No 8496 (94.03%) 3762 (95.39) 3554 (93.48) 1180 (91.54) Yes 539 (5.97%) 182 (4.61) 248 (6.52) 109 (8.46) Hypertension, N (%) < 0.05 No 5601 (61.99%) 2540 (64.40) 2326 (61.18) 735 (57.02) Yes 3434 (38.01%) 1404 (35.60) 1476 (38.82) 554 (42.98) 3.2. Association Between HI and the Risk of CMM During the 7-year follow-up period, 382 participants developed CMM, with a cumulative incidence rate of 4.23%. Cox proportional hazards regression model revealed a significant positive association between the degree of HI and the risk of CMM, which remained independent of potential confounding factors, as shown in Table 2 . In Model 1, compared with the normal hearing group, both the mild HI group (HR = 1.31, 95% CI: 1.05–1.64) and the severe HI group (HR = 1.55, 95% CI: 1.16–2.07) exhibited a significantly elevated risk of CMM (all P < 0.05). The association remained significant after adjusting for model 2. In Model 3, compared with the normal hearing group, both the mild HI group (HR = 1.30, 95% CI: 1.03–1.63) and the severe HI group (HR = 1.53, 95% CI: 1.14–2.06) exhibited a significantly elevated risk of CMM (all P < 0.05). These results indicated a strong association between HI and the risk of CMM, as shown in Table 2 . Table 2 Cox proportional hazards regression between HI and CMM Hearing status Model 1 (Unadjusted) Model 2 (Adjusted for age and sex) Model 3 (Fully adjusted) HR (95% CI) P HR (95% CI) P HR (95% CI) P Normal hearing Reference Reference Reference Mild HI 1.31 (1.05–1.64) 0.017 1.29 (1.03–1.61) 0.028 1.30 (1.03–1.63) 0.025 Severe HI 1.55 (1.16–2.07) 0.003 1.49 (1.11–2.00) 0.008 1.53 (1.14–2.06) 0.005 The Kaplan–Meier survival curves (Fig. 2) intuitively illustrate the significant differences in the occurrence rate of CMM among groups with different hearing statuses, with the severe HI group exhibited the highest cumulative incidence rate. 3.3. Subgroup Analysis and Interaction Tests To explore the heterogeneity of the association between HI and CMM across different populations, subgroup analyses were stratified by age (45–60 years/≥60 years) and sex (male/female). After adjustment for all covariates, females exhibited a significantly higher risk of both mild HI (HR = 1.51, 95% CI: 1.11–2.07) and severe HI (HR = 1.56, 95% CI: 1.03–2.37) compared with males. No significant interaction was observed between sex and the degree of HI ( P for interaction = 0.34). Participants aged ≥ 60 years had a significantly higher risk of severe HI than those aged 45–60 years (HR = 1.69, 95% CI: 1.14–2.51), while no significant difference emerged for mild HI (HR = 1.37, 95% CI : 0.97–1.94). No significant interaction was observed between age and the degree of HI ( P for interaction = 0.67). (Table 3 ) Table 3 Subgroup analysis of CMM risk by hearing status and interaction tests Variable Normal hearing HR(95% CI ) Mild HI HR(95% CI ) Severe HI HR(95% CI ) P for interaction Sex 0.34 Male 1 (reference) 1.12(0.80–1.57) 1.50(0.99–2.29) Female 1 (reference) 1.51(1.11–2.07) 1.56(1.03–2.37) Age 0.67 45–60 years 1 (reference) 1.28(0.95–1.73) 1.32(0.82–2.12) ≥ 60 years 1 (reference) 1.37(0.97–1.94) 1.69(1.14–2.51) 4. Discussion Using a nationally representative sample from the CHARLS database, this study included 9,035 participants to investigate the association between HI and the risk of CMM in middle-aged and older adults. The results demonstrated that HI was associated with an elevated risk of CMM, and this association was more pronounced among females and individuals aged 60 years or older. These findings provide new insights into the identification of risk factors for CMM and the early screening of high-risk populations. This national cohort study first identified HI as an independent risk factor for CMM. In the fully adjusted model, individuals with mild and severe HI showed a 30% and 53% elevated risk of CMM, respectively. This indicated that HI may be an early warning signal for the development of CMM. This finding aligns with previous studies suggesting an association between HL and CVD 12 . A previous meta-analysis demonstrated that HL significantly increases the risk of cardiovascular mortality by 28% (HR = 1.28, 95% CI: 1.10–1.50) 18 . A dose-response relationship was also identified, showing that each 30-dB increment in audiometric thresholds doubles the hazard for all-cause mortality (HR = 2.05, 95% CI: 1.45–2.90) 18 . The results confirm the observed dose-response relationship between HL severity and risk elevation, where the hazard increases progressively with higher audiometric thresholds in a dose-dependent relationship. Kim et al. confirmed a significant positive correlation between the degree of HL and the risk of CVD in occupational noise-exposed populations 19 . A Korean longitudinal study further substantiated this association within specific populations. For instance, among individuals with diabetes and comorbid hearing impairment, the risk of myocardial infarction rose by 11.7% and that of stroke by 13.4% 20 . This study demonstrates that HI was an independent risk factor for the development of CMM in middle-aged and older adults, and its underlying mechanisms involve the synergistic effects of multiple pathophysiological pathways, including behavioral patterns, vascular pathology, inflammatory stress, and psychoneuroendocrine responses. Firstly, changes in behavioral patterns represent important driving factors. ‌Specifically, communication barriers caused by moderate to severe hearing loss can lead to ‌social isolation‌, which in turn may discourage participation in physical activities 21 , and the decrease in physical activities can lead to the development of metabolic disorders, including obesity and insulin resistance 22−23 . These findings indicate that exercise interventions for individuals with HI might lower the risk of CMM. Secondly, CVD and HI are directly related through a common vascular pathological basis. The high metabolic characteristics of microcirculation in the inner ear make stria vascularis highly sensitive to ischemia and hypoxia 22 . Vascular dysfunction represents a core pathological mechanism in CMM, which can simultaneously compromise cochlear perfusion and disrupt cardiovascular and cerebral blood supply. Furthermore, after adjusting for factors including smoking status and hypertension, the association remained significant, suggesting that pathological mechanisms independent of established vascular risk factors may be involved. Thirdly, chronic inflammation and oxidative stress play pivotal roles in this process. The elevation of inflammatory markers such as interleukin-6 and C-reactive protein is associated not only with HL, but also serves as a key trigger for the development of CMM 24−26 . HL may trigger systemic inflammation through persistent sensory damage or by reducing anti-inflammatory factors due to social withdrawal. This establishes a vicious cycle of "inflammation-metabolic disorders-vascular injury," which exacerbates hearing deterioration and increases cardiometabolic risk. Finally, psychological and neuroendocrine disorders exert a cumulative effect. Negative emotions such as depression and anxiety caused by HI, promote abnormal vasoconstriction and hemorheological alterations through neuroendocrine pathways involving imbalance of the 5-hydroxytryptamine and norepinephrine, ultimately inducing tissue ischemia and hypoxia and increasing the risk of cardiovascular events 27 . The overlapping risk factors, including advanced age and unhealthy diet, further amplify these effects through multisystem interactions. This study further explored the differences in the association between HI and CMM risk using stratified analyses by sex and age. Results from the sex subgroup analysis revealed that among females, the risk of CMM was 51% higher in those with mild HI than in those with normal hearing (OR = 1.51, 95% CI: 1.11-2.0), while severe HI was associated with a further elevated risk of 56% (OR = 1.56, 95% CI: 1.03–2.37). In contrast, no statistically significant association was observed among male participants. statistically significant association was observed among male participants. This observed sex difference aligns with findings from other studies on CVD associated with sensory impairments. A cross-sectional study from Bulgaria found that women exposed to self-reported occupational noise exhibited a 26% increased risk of heart disease (relative risk [RR] = 1.26, 95% CI: 0.53–3.01), whereas no significant risk change was observed in men (RR = 0.49, 95% CI: 0.14–1.65) 28 . In this study, the strong association between HI and the risk of CMM in women over 45 years of age may be related to sex differences and the regulatory role of estrogen. Compared with men, women exhibit higher peak amplitudes and shorter latencies of auditory evoked potentials, as well as lower hearing thresholds, suggesting physiological advantages in cochlear sensitivity and neural conduction velocity. 29 – 30 Furthermore, estrogen exerts protective effects on both the cardiovascular system and auditory function 31 . Elevated circulating estrogen levels delay age-related HL and mitigate the risk of CVDs by maintaining cochlear tissue integrity, modulating metabolism, suppressing oxidative stress, and promoting angiogenesis 32 – 33 . Following menopause, the sharp decline in estrogen levels not only accelerates the deterioration of auditory function but may also exacerbate metabolic disorders and CVD risk through the aforementioned physiological pathways. This mechanism may significantly contribute to the more pronounced association between HI and CMM risk observed in females in this study. Age-stratified analysis revealed a 69% increased risk of CMM (OR = 1.69, 95% CI:1.14–2.51) in individuals aged ≥ 60 years with severe HI compared to those with normal hearing, while no significant association was observed among participants aged 45–60 years. This result may be associated with the age-dependent increase in CMM risk. With advancing age, the decline in metabolic function, accumulation of chronic inflammation, and reduction in physiological reserves across multiple systems collectively contribute to an elevated risk of CMM development. As the first longitudinal cohort study in China to examine the association between HI and the incidence of CMM, this research addresses an important gap in epidemiological evidence and offers a theoretical foundation for identifying CMM risk factors and screening high-risk populations. Furthermore, this study draws on a nationally representative sample from the CHARLS database, which includes middle-aged and older adults across diverse regions, urban and rural settings, and socioeconomic strata in China. The results demonstrate strong extrapolation and effectively circumvent the regional selection bias inherent in single-center studies. This study employed a multifactorial Cox proportional hazards regression model to adjust for potential confounders, including demographic characteristics (including age, sex, education level, and marital status), lifestyle factors (including smoking history, alcohol use history), BMI, and medical history (including hypertension, CKD). Stratified analyses by sex and age were further conducted to assess the stability of the associations, which strengthens the internal validity of the findings. However, this study has several limitations. The definition of Hearing status relied on self-reported questionnaires or pure-tone audiometry, potentially introducing classification bias, and the self-reported data are inherently susceptible to subjective perception. In addition, the CHARLS database lacks information on specific etiologies of HL, such as occupational noise exposure or the use of ototoxic medications, making it impossible to further analyze the differences in the association between different types of HI and the risk of CMM. Although this study adjusted for multiple covariates, residual confounding from unmeasured factors (e.g., dietary patterns, physical activity intensity, or baseline cardiovascular health status) may persist, potentially influencing the observed associations. Thus, future intervention studies are needed to address these limitations and validate the findings. In summary, this study provides epidemiological evidence linking HI to CMM. However, further large-scale, multicenter prospective studies are needed to clarify the causal relationship and identify potential interventional targets, which should incorporate etiological classification of HI and exploration of molecular mechanisms. Abbreviations CMM: cardiometabolic multimorbidity; CMD: cardiometabolic disease; CVD: cardiovascular disease; HI: Hearing impairment; HI: hearing loss; OR: Odds Ratio; CI: confidence interval; CHARLS: China Health and Retirement Longitudinal Study; CKD: chronic kidney disease; BMI: body mass index; SD: standard deviation; HR: hazard ratio; RR: relative risk. Declarations Competing interests: The authors declare no competing interests. Funding: This study received no funding. Author Contribution X-D Z collected and analyzed the data. Q-C Z drafted the manuscript. B D, Z-J P, and Y-Z S assessed the methodological quality and data integrity of the included studies. 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Endocrinol. 10.1038/nrendo.2017.12 (2017). Andrea, I. et al. The protective role of estrogen and estrogen receptors in cardiovascular disease and the controversial use of estrogen therapy. Biol. Sex. Differ. 10.1186/s13293-017-0152-8 (2017). Additional Declarations No competing interests reported. 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qia-chun","middleName":"","lastName":"Zhang","suffix":""},{"id":551973400,"identity":"671d1c8d-4381-4f9a-a55e-adc27d9c0633","order_by":2,"name":"Bin Deng","email":"","orcid":"","institution":"Shenzhen Bao'an Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Deng","suffix":""},{"id":551973401,"identity":"b386dfe5-0df3-4657-a46f-39d53691c3ce","order_by":3,"name":"Zhi-jian Peng","email":"","orcid":"","institution":"Shenzhen Bao'an Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhi-jian","middleName":"","lastName":"Peng","suffix":""},{"id":551973402,"identity":"d7dbd65c-2ac8-4a8e-ab53-9b87cdc18407","order_by":4,"name":"Yin-zhi Song","email":"","orcid":"","institution":"Shenzhen Bao'an Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yin-zhi","middleName":"","lastName":"Song","suffix":""},{"id":551973403,"identity":"078c0584-ee8c-47e0-96c3-ed3f8015dfb7","order_by":5,"name":"Yao-ping Tang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDElEQVRIiWNgGAWjYPACGx42hsMH4FwJfGp5IFSaHB/jsQQGhgTitRw2lmM+Y0CcFnv2s4df8+5gTmxjO/P5Ne8Pu2iDA8wHb/Mw2OXhtIUnL82a9wxbYhvP2W2WMxKSczccYEu25mFILsbtsBwzY942nsQ2ibPbDD4kHABq4TGT5mE4kNiASwv/G5AWicQ2+TfPDBLAWvi/4dcikWP8mLfNwJiN4QzzA6gtbPi13Hhjxjj3TIIcG8MxM8YZacm5Mw+zGVvOMUjGqYW9P8f4w9sd/3nkGw4//sxjY5fbd7z54Y03FXY4tQABmxQvRJYNEh3MIMIAt3qQko8/IVqYP+BVNwpGwSgYBSMWAACt6lnTNKUecwAAAABJRU5ErkJggg==","orcid":"","institution":"Guangxi University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Yao-ping","middleName":"","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2025-10-22 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1","display":"","copyAsset":false,"role":"figure","size":36233,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7920636/v1/248b4437e040a22cb03e3c11.png"},{"id":97257687,"identity":"4566d804-b58b-43bf-891c-4b8339b12d7a","added_by":"auto","created_at":"2025-12-02 13:41:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":10931,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7920636/v1/c7f1de02d19afb9e94dd321c.png"},{"id":106343383,"identity":"cf27c2b4-11ca-4ebe-b289-ba419c06a53d","added_by":"auto","created_at":"2026-04-07 16:04:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":893207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7920636/v1/b5bcac4d-306e-4fe2-a9c2-fe084c41cee1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association Between Hearing Impairment and Cardiometabolic Multimorbidity Among Middle-Aged and Older Adults in China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCardiometabolic multimorbidity (CMM) refers to the coexistence of two or more cardiometabolic diseases (CMD), such as diabetes, cardiovascular disease (CVD), and stroke\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. With the accelerating aging of the global population, the prevalence of CMM has risen significantly, establishing it as a major public health issue that threatens the health of middle-aged and older adults\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Compared to individuals with a single CMD, those with CMM face substantially higher risks of all-cause mortality, recurrent cardiovascular events, and healthcare resource utilization, imposing a considerable burden on healthcare systems\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Therefore, identifying modifiable risk factors for CMM and developing early intervention strategies are of significant clinical importance.\u003c/p\u003e\u003cp\u003eHearing impairment (HI) is a highly prevalent sensory disorder in older adults and represents the third leading cause of disability globally\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, and its incidence increases with age. Approximately 1.57\u0026nbsp;billion people globally experienced some degree of hearing loss (HL) in 2019, representing 19.3% of the world's population\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Among adults aged 60 years and older, the prevalence of disabling HL surpasses 25%\u003csup\u003e10\u003c/sup\u003e. In recent years, the association between HI and systemic chronic disorders has garnered increasing attention, particularly in the field of cardiometabolic health. Previous studies have indicated that individuals with HI have a 20% increased risk of developing CVD compared to those with normal hearing\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, the underlying mechanisms may be associated with pathophysiological pathways such as cochlear microvascular ischemia, chronic inflammation, and oxidative stress\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Furthermore, a cross-sectional study revealed a significantly higher risk of CMM among individuals with dual impairment of sensory vision and hearing (odds ratio [OR]\u0026thinsp;=\u0026thinsp;1.862, 95% confidence interval [CI]: 1.387\u0026ndash;2.500)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, the independent association between HI with CMM and their dose-response relationship remain unclear. This study employs nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS) to systematically examine the association between HI and CMM, aiming to establish a scientific foundation for early prevention and screening of high-risk populations for CMM.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data and sample sources\u003c/h2\u003e\u003cp\u003eThe data for this study were derived from the CHARLS. CHARLS is a nationally representative prospective cohort study of middle-aged and older adults (\u0026ge;\u0026thinsp;45 years) in China. Its sampling framework spans 28 provinces, 150 county-level units, and 450 village-level units, ensuring strong regional and population representativeness\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The study encompasses comprehensive assessments of sociodemographic characteristics (e.g., age, sex, education level), health status and functioning (e.g., history of chronic diseases, hearing function, and activities of daily living), and socioeconomic status (e.g., income, health insurance coverage). CHARLS data collection began with the baseline survey in 2011, and follow-up surveys were conducted in 2013, 2015, 2018, and 2020. The baseline survey was initiated in 2011, with follow-up surveys conducted in 2013, 2015, 2018, and 2020. The CHARLS was approved by the Biomedical Ethics Committee of Peking University (IRB00001052-11015). All participants provided written informed consent. The datasets can be accessed through the official website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://charls.pku.edu.cn/en/\u003c/span\u003e\u003cspan address=\"http://charls.pku.edu.cn/en/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study employed data from the CHARLS spanning from 2011 to 2018 to analysis. The inclusion criteria were as follows: (1) age\u0026thinsp;\u0026ge;\u0026thinsp;45 years; (2) completion of hearing function assessment and cardiometabolic-related evaluations at baseline survey; and (3) availability of complete clinical data. The exclusion criteria were as follows: (1) age\u0026thinsp;\u0026lt;\u0026thinsp;45 years (n\u0026thinsp;=\u0026thinsp;649); (2) missing data on key covariate information (e.g., sex, marital status, education level, smoking history and alcohol use history, n\u0026thinsp;=\u0026thinsp;3952); (3) incomplete data on chronic disease history (including hypertension, diabetes, heart disease, stroke, and chronic kidney disease [CKD], n\u0026thinsp;=\u0026thinsp;217); (4) pre-existing CMM at baseline survey (n\u0026thinsp;=\u0026thinsp;400); and (5) death or loss to follow-up during the study period (n\u0026thinsp;=\u0026thinsp;3445). Ultimately, a total of 9,035 participants were included in the analysis. The detailed screening process is illustrated in Fig.\u0026nbsp;1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Assessment of Hearing status and CMM\u003c/h2\u003e\u003cp\u003eHearing function was evaluated with a standardized question from the CHARLS questionnaire: \u0026ldquo;Is your hearing excellent, very good, good, fair, or poor (with using hearing aid if they use)?\u0026rdquo; \u003csup\u003e15\u003c/sup\u003e. Hearing status was classified into three groups based on established diagnostic criteria\u0026zwnj;\u003csup\u003e7, 1\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e: normal hearing (self-reported \u0026ldquo;excellent,\u0026rdquo; \u0026ldquo;very good,\u0026rdquo; or \u0026ldquo;good\u0026rdquo;), mild HI (self-reported \u0026ldquo;fair\u0026rdquo;), and severe HI (self-reported \u0026ldquo;poor\u0026rdquo; or daily use of hearing aid).\u003c/p\u003e\u003cp\u003eThe presence of CMD was assessed through self-reported physician diagnosis of any of the following conditions: (1) diabetes or hyperglycemia; (2) stroke; (3) CVD (including coronary heart disease, angina, congestive heart failure, or other cardiac disorders)\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. CMM was defined as the concurrent presence of two or more CMD during follow-up.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Assessment of Covariates\u003c/h2\u003e\u003cp\u003eThe covariates included in this study encompassed demographic characteristics (including age, sex, education level, marital status), lifestyle factors (including smoking history, alcohol use history), body mass index (BMI), and medical history (including hypertension, CKD). Education level was reclassified from the original 12 categories into four levels: illiterate, primary school, junior high school, and high school or above. Marital status was categorized into married/cohabiting and other (including divorced, widowed, and unmarried). Smoking and alcohol use histories were recorded as binary variables (yes/no). BMI was calculated as weight (kg) divided by the square of height (m). Medical history of hypertension and CKD was determined based on self-reported physician diagnoses. All covariate data were obtained from standardized questionnaires and physical examination records to ensure data consistency and completeness.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Statistical Analysis\u003c/h2\u003e\u003cp\u003eNormally distributed continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and compared using the t-test. Non-normally distributed continuous variables were expressed as median and interquartile range and compared using the Mann-Whitney U test. Categorical variables were presented as frequencies and percentages and compared between groups using Fisher\u0026rsquo;s exact test or Pearson\u0026rsquo;s chi-square test, as appropriate. The Kaplan\u0026ndash;Meier survival curves were used to describe the cumulative incidence risk of CMM for different hearing status groups, and differences between groups were compared using the log-rank test. Cox proportional hazards regression model were used to calculate hazard ratio (HR) and 95% CI for the association between hearing status and CMM. The following three models were constructed: Model 1 was unadjusted; Model 2 was adjusted for age and sex; and Model 3 was further adjusted for smoking history, alcohol use history, education level, marital status, BMI, hypertension, and CKD based on Model 2.\u003c/p\u003e\u003cp\u003eTo verify the robustness of the results, subgroup analyses were stratified by age (45\u0026ndash;60 years/\u0026ge;60 years) and sex (male/female) to explore the heterogeneity of the association between HI and CMM across different populations. All tests were two-sided, and a \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Data analysis was performed using Zstats software (version 1.0; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.zstats.net\u003c/span\u003e\u003cspan address=\"http://www.zstats.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and R (version 4.3.3).\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Baseline Characteristics of study participants\u003c/h2\u003e\u003cp\u003e A total of 9,035 participants aged 45 years or older were included in this study, including 3,944 participants (43.65%) in the normal hearing group, 3,802 participants (42.08%) in the mild HI group, and 1,289 participants (14.27%) in the severe HI group. Statistically significant differences were observed in the three groups in terms of age, BMI, smoking history, alcohol use history, marital status, education level, prevalence of hypertension and CKD (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The normal hearing group was younger (57.07\u0026thinsp;\u0026plusmn;\u0026thinsp;8.40 years), had a lower prevalence of hypertension (35.6%) and CKD (4.61%), and a higher education level (12.91% with high school or above) at baseline. In contrast, the severe HI group was older (62.30\u0026thinsp;\u0026plusmn;\u0026thinsp;9.38 years), had a higher prevalence of hypertension (42.98%), and a lower education level (40.11% with illiterate). The baseline characteristics of study participants are depicted in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBaseline characteristics of study participants\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;9,035\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNormal hearing\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;3,944\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMild HI\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;3,802\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSevere HI\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;1,289\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58.57\u0026thinsp;\u0026plusmn;\u0026thinsp;8.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57.07\u0026thinsp;\u0026plusmn;\u0026thinsp;8.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58.86\u0026thinsp;\u0026plusmn;\u0026thinsp;8.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62.30\u0026thinsp;\u0026plusmn;\u0026thinsp;9.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex, N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4167 (46.12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1873 (47.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1707 (44.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e587 (45.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4868 (53.88%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2071 (52.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2095 (55.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e702 (54.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI, N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;24 kg/m\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6245 (69.12%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2663 (67.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2624 (69.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e958 (74.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;24 kg/m\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2790 (30.88%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1281 (32.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1178 (30.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e331 (25.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol use history, N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6049 (66.95%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2575 (65.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2568 (67.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e906 (70.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2986 (33.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1369 (34.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1234 (32.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e383 (29.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking history, N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6253 (69.21%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2671 (67.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2670 (70.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e912 (70.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2782 (30.79%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1273 (32.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1132 (29.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e377 (29.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status, N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e947 (10.48%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e380 (9.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e380 (9.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e187 (14.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried/cohabiting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8088 (89.52%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3564 (90.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3422 (90.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1102 (85.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducational level, N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIlliterate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2535 (28.06%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e993 (25.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1025 (26.96)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e517 (40.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3743 (41.43%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1528 (38.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1681 (44.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e534 (41.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1850 (20.48%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e914 (23.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e773 (20.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e163 (12.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school or above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e907 (10.04%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e509 (12.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e323 (8.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e75 (5.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCKD, N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8496 (94.03%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3762 (95.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3554 (93.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1180 (91.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e539 (5.97%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e182 (4.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e248 (6.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e109 (8.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension, N (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5601 (61.99%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2540 (64.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2326 (61.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e735 (57.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3434 (38.01%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1404 (35.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1476 (38.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e554 (42.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Association Between HI and the Risk of CMM\u003c/h2\u003e\u003cp\u003eDuring the 7-year follow-up period, 382 participants developed CMM, with a cumulative incidence rate of 4.23%. Cox proportional hazards regression model revealed a significant positive association between the degree of HI and the risk of CMM, which remained independent of potential confounding factors, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In Model 1, compared with the normal hearing group, both the mild HI group (HR\u0026thinsp;=\u0026thinsp;1.31, 95% CI: 1.05\u0026ndash;1.64) and the severe HI group (HR\u0026thinsp;=\u0026thinsp;1.55, 95% CI: 1.16\u0026ndash;2.07) exhibited a significantly elevated risk of CMM (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The association remained significant after adjusting for model 2. In Model 3, compared with the normal hearing group, both the mild HI group (HR\u0026thinsp;=\u0026thinsp;1.30, 95% CI: 1.03\u0026ndash;1.63) and the severe HI group (HR\u0026thinsp;=\u0026thinsp;1.53, 95% CI: 1.14\u0026ndash;2.06) exhibited a significantly elevated risk of CMM (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These results indicated a strong association between HI and the risk of CMM, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCox proportional hazards regression between HI and CMM\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHearing status\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003cp\u003e(Unadjusted)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003cp\u003e(Adjusted for age and sex)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003cp\u003e(Fully adjusted)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal hearing\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMild HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.31 (1.05\u0026ndash;1.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.29 (1.03\u0026ndash;1.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.30 (1.03\u0026ndash;1.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSevere HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.55 (1.16\u0026ndash;2.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.49 (1.11\u0026ndash;2.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.53 (1.14\u0026ndash;2.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe Kaplan\u0026ndash;Meier survival curves (Fig.\u0026nbsp;2) intuitively illustrate the significant differences in the occurrence rate of CMM among groups with different hearing statuses, with the severe HI group exhibited the highest cumulative incidence rate.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Subgroup Analysis and Interaction Tests\u003c/h2\u003e\u003cp\u003eTo explore the heterogeneity of the association between HI and CMM across different populations, subgroup analyses were stratified by age (45\u0026ndash;60 years/\u0026ge;60 years) and sex (male/female). After adjustment for all covariates, females exhibited a significantly higher risk of both mild HI (HR\u0026thinsp;=\u0026thinsp;1.51, 95% CI: 1.11\u0026ndash;2.07) and severe HI (HR\u0026thinsp;=\u0026thinsp;1.56, 95% CI: 1.03\u0026ndash;2.37) compared with males. No significant interaction was observed between sex and the degree of HI (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.34). Participants aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years had a significantly higher risk of severe HI than those aged 45\u0026ndash;60 years (HR\u0026thinsp;=\u0026thinsp;1.69, 95% CI: 1.14\u0026ndash;2.51), while no significant difference emerged for mild HI (HR\u0026thinsp;=\u0026thinsp;1.37, 95% \u003cem\u003eCI\u003c/em\u003e: 0.97\u0026ndash;1.94). No significant interaction was observed between age and the degree of HI (\u003cem\u003eP\u003c/em\u003e for interaction\u0026thinsp;=\u0026thinsp;0.67). (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSubgroup analysis of CMM risk by hearing status and interaction tests\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal hearing\u003c/p\u003e\u003cp\u003eHR(95%\u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMild HI\u003c/p\u003e\u003cp\u003eHR(95%\u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSevere HI\u003c/p\u003e\u003cp\u003eHR(95%\u003cem\u003eCI\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.12(0.80\u0026ndash;1.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.50(0.99\u0026ndash;2.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.51(1.11\u0026ndash;2.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.56(1.03\u0026ndash;2.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;60 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.28(0.95\u0026ndash;1.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.32(0.82\u0026ndash;2.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;60 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.37(0.97\u0026ndash;1.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.69(1.14\u0026ndash;2.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eUsing a nationally representative sample from the CHARLS database, this study included 9,035 participants to investigate the association between HI and the risk of CMM in middle-aged and older adults. The results demonstrated that HI was associated with an elevated risk of CMM, and this association was more pronounced among females and individuals aged 60 years or older. These findings provide new insights into the identification of risk factors for CMM and the early screening of high-risk populations.\u003c/p\u003e\u003cp\u003eThis national cohort study first identified HI as an independent risk factor for CMM. In the fully adjusted model, individuals with mild and severe HI showed a 30% and 53% elevated risk of CMM, respectively. This indicated that HI may be an early warning signal for the development of CMM. This finding aligns with previous studies suggesting an association between HL and CVD\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. A previous meta-analysis demonstrated that HL significantly increases the risk of cardiovascular mortality by 28% (HR\u0026thinsp;=\u0026thinsp;1.28, 95% CI: 1.10\u0026ndash;1.50)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. A dose-response relationship was also identified, showing that each 30-dB increment in audiometric thresholds doubles the hazard for all-cause mortality (HR\u0026thinsp;=\u0026thinsp;2.05, 95% CI: 1.45\u0026ndash;2.90)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The results confirm the observed dose-response relationship between HL severity and risk elevation, where the hazard increases progressively with higher audiometric thresholds in a dose-dependent relationship. Kim et al. confirmed a significant positive correlation between the degree of HL and the risk of CVD in occupational noise-exposed populations\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. A Korean longitudinal study further substantiated this association within specific populations. For instance, among individuals with diabetes and comorbid hearing impairment, the risk of myocardial infarction rose by 11.7% and that of stroke by 13.4%\u003csup\u003e20\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study demonstrates that HI was an independent risk factor for the development of CMM in middle-aged and older adults, and its underlying mechanisms involve the synergistic effects of multiple pathophysiological pathways, including behavioral patterns, vascular pathology, inflammatory stress, and psychoneuroendocrine responses. Firstly, changes in behavioral patterns represent important driving factors. \u0026zwnj;Specifically, communication barriers caused by moderate to severe hearing loss can lead to \u0026zwnj;social isolation\u0026zwnj;, which in turn may discourage participation in physical activities\u003csup\u003e21\u003c/sup\u003e, and the decrease in physical activities can lead to the development of metabolic disorders, including obesity and insulin resistance\u003csup\u003e22\u0026minus;23\u003c/sup\u003e. These findings indicate that exercise interventions for individuals with HI might lower the risk of CMM. Secondly, CVD and HI are directly related through a common vascular pathological basis. The high metabolic characteristics of microcirculation in the inner ear make stria vascularis highly sensitive to ischemia and hypoxia\u003csup\u003e22\u003c/sup\u003e. Vascular dysfunction represents a core pathological mechanism in CMM, which can simultaneously compromise cochlear perfusion and disrupt cardiovascular and cerebral blood supply. Furthermore, after adjusting for factors including smoking status and hypertension, the association remained significant, suggesting that pathological mechanisms independent of established vascular risk factors may be involved. Thirdly, chronic inflammation and oxidative stress play pivotal roles in this process. The elevation of inflammatory markers such as interleukin-6 and C-reactive protein is associated not only with HL, but also serves as a key trigger for the development of CMM\u003csup\u003e24\u0026minus;26\u003c/sup\u003e. HL may trigger systemic inflammation through persistent sensory damage or by reducing anti-inflammatory factors due to social withdrawal. This establishes a vicious cycle of \"inflammation-metabolic disorders-vascular injury,\" which exacerbates hearing deterioration and increases cardiometabolic risk. Finally, psychological and neuroendocrine disorders exert a cumulative effect. Negative emotions such as depression and anxiety caused by HI, promote abnormal vasoconstriction and hemorheological alterations through neuroendocrine pathways involving imbalance of the 5-hydroxytryptamine and norepinephrine, ultimately inducing tissue ischemia and hypoxia and increasing the risk of cardiovascular events\u003csup\u003e27\u003c/sup\u003e. The overlapping risk factors, including advanced age and unhealthy diet, further amplify these effects through multisystem interactions.\u003c/p\u003e\u003cp\u003eThis study further explored the differences in the association between HI and CMM risk using stratified analyses by sex and age. Results from the sex subgroup analysis revealed that among females, the risk of CMM was 51% higher in those with mild HI than in those with normal hearing (OR\u0026thinsp;=\u0026thinsp;1.51, 95% CI: 1.11-2.0), while severe HI was associated with a further elevated risk of 56% (OR\u0026thinsp;=\u0026thinsp;1.56, 95% CI: 1.03\u0026ndash;2.37). In contrast, no statistically significant association was observed among male participants. statistically significant association was observed among male participants. This observed sex difference aligns with findings from other studies on CVD associated with sensory impairments. A cross-sectional study from Bulgaria found that women exposed to self-reported occupational noise exhibited a 26% increased risk of heart disease (relative risk [RR]\u0026thinsp;=\u0026thinsp;1.26, 95% CI: 0.53\u0026ndash;3.01), whereas no significant risk change was observed in men (RR\u0026thinsp;=\u0026thinsp;0.49, 95% CI: 0.14\u0026ndash;1.65)\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In this study, the strong association between HI and the risk of CMM in women over 45 years of age may be related to sex differences and the regulatory role of estrogen. Compared with men, women exhibit higher peak amplitudes and shorter latencies of auditory evoked potentials, as well as lower hearing thresholds, suggesting physiological advantages in cochlear sensitivity and neural conduction velocity.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Furthermore, estrogen exerts protective effects on both the cardiovascular system and auditory function\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Elevated circulating estrogen levels delay age-related HL and mitigate the risk of CVDs by maintaining cochlear tissue integrity, modulating metabolism, suppressing oxidative stress, and promoting angiogenesis\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Following menopause, the sharp decline in estrogen levels not only accelerates the deterioration of auditory function but may also exacerbate metabolic disorders and CVD risk through the aforementioned physiological pathways. This mechanism may significantly contribute to the more pronounced association between HI and CMM risk observed in females in this study. Age-stratified analysis revealed a 69% increased risk of CMM (OR\u0026thinsp;=\u0026thinsp;1.69, 95% CI:1.14\u0026ndash;2.51) in individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years with severe HI compared to those with normal hearing, while no significant association was observed among participants aged 45\u0026ndash;60 years. This result may be associated with the age-dependent increase in CMM risk. With advancing age, the decline in metabolic function, accumulation of chronic inflammation, and reduction in physiological reserves across multiple systems collectively contribute to an elevated risk of CMM development.\u003c/p\u003e\u003cp\u003eAs the first longitudinal cohort study in China to examine the association between HI and the incidence of CMM, this research addresses an important gap in epidemiological evidence and offers a theoretical foundation for identifying CMM risk factors and screening high-risk populations. Furthermore, this study draws on a nationally representative sample from the CHARLS database, which includes middle-aged and older adults across diverse regions, urban and rural settings, and socioeconomic strata in China. The results demonstrate strong extrapolation and effectively circumvent the regional selection bias inherent in single-center studies. This study employed a multifactorial Cox proportional hazards regression model to adjust for potential confounders, including demographic characteristics (including age, sex, education level, and marital status), lifestyle factors (including smoking history, alcohol use history), BMI, and medical history (including hypertension, CKD). Stratified analyses by sex and age were further conducted to assess the stability of the associations, which strengthens the internal validity of the findings. However, this study has several limitations. The definition of Hearing status relied on self-reported questionnaires or pure-tone audiometry, potentially introducing classification bias, and the self-reported data are inherently susceptible to subjective perception. In addition, the CHARLS database lacks information on specific etiologies of HL, such as occupational noise exposure or the use of ototoxic medications, making it impossible to further analyze the differences in the association between different types of HI and the risk of CMM. Although this study adjusted for multiple covariates, residual confounding from unmeasured factors (e.g., dietary patterns, physical activity intensity, or baseline cardiovascular health status) may persist, potentially influencing the observed associations. Thus, future intervention studies are needed to address these limitations and validate the findings.\u003c/p\u003e\u003cp\u003eIn summary, this study provides epidemiological evidence linking HI to CMM. However, further large-scale, multicenter prospective studies are needed to clarify the causal relationship and identify potential interventional targets, which should incorporate etiological classification of HI and exploration of molecular mechanisms.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCMM: cardiometabolic multimorbidity; CMD: cardiometabolic disease; CVD: cardiovascular disease; HI: Hearing impairment; HI: hearing loss;\u003c/p\u003e\n\u003cp\u003eOR: Odds Ratio; CI: confidence interval; CHARLS: China Health and Retirement Longitudinal Study; CKD: chronic kidney disease; BMI: body mass index; SD: standard deviation; HR: hazard ratio; RR: relative risk.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting interests:\u003c/h2\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis study received no funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eX-D Z collected and analyzed the data. Q-C Z drafted the manuscript. B D, Z-J P, and Y-Z S assessed the methodological quality and data integrity of the included studies. Y-P T provided critical feedback and revisions throughout the manuscript's development. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the CHARLS database for providing the data.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data for this study originated from a publicly available database.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMika, K. et al. Overweight, obesity, and risk of cardiometabolic multimorbidity: pooled analysis of individual-level data for 120 813 adults from 16 cohort studies from the USA and Europe. \u003cem\u003eLancet Public. 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Differ.\u003c/em\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13293-017-0152-8\u003c/span\u003e\u003cspan address=\"10.1186/s13293-017-0152-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Hearing impairment, Cardiometabolic Multimorbidity, Middle-Aged and Older Adults, China Health and Retirement Longitudinal Study, Cohort Study","lastPublishedDoi":"10.21203/rs.3.rs-7920636/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7920636/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study examined the association between hearing impairment (HI) and the risk of cardiometabolic multimorbidity (CMM) in middle-aged and older adults, providing evidence to support early warning and screening of high-risk CMM populations. This study analyzed data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011 to 2018. The analysis included 9,035 participants aged 45 years and older. The association between HI and the risk of CMM was investigated using multivariable Cox proportional hazards regression, Kaplan\u0026ndash;Meier survival curves, and subgroup analyses. The results were as follows: Over a median follow-up of 7 years, 382 incident CMM cases were documented. Compared to individuals with normal hearing, those with mild HI had a 31% increased risk of CMM (Hazard Ratio [HR]\u0026thinsp;=\u0026thinsp;1.31, 95% Confidence Interval [CI]: 1.04\u0026ndash;1.64), while those with severe HI had a 56% increased risk (HR\u0026thinsp;=\u0026thinsp;1.56, 95% CI: 1.16\u0026ndash;2.10). Subgroup analyses revealed that among women, the risk of CMM was significantly elevated by 51% (HR\u0026thinsp;=\u0026thinsp;1.51, 95% CI: 1.11-2.00) for mild HI and by 56% (HR\u0026thinsp;=\u0026thinsp;1.56, 95% CI: 1.03\u0026ndash;2.37) for severe HI. Among individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years, severe HI was associated with a 69% increased risk (HR\u0026thinsp;=\u0026thinsp;1.69, 95% CI: 1.14\u0026ndash;2.51). However, no statistically significant associations were observed in men or in the 45\u0026ndash;60 age group (\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05). Our findings suggest that HI is an independent risk factor for incident CMM in middle-aged and older adults, with the association being more pronounced in women and individuals aged 60 years or older.\u003c/p\u003e","manuscriptTitle":"Association Between Hearing Impairment and Cardiometabolic Multimorbidity Among Middle-Aged and Older Adults in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 13:41:24","doi":"10.21203/rs.3.rs-7920636/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-17T13:08:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-01T21:28:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-25T23:28:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"222132529091317017503261553827024340052","date":"2025-11-25T23:22:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78897670715236449363569897070810338244","date":"2025-11-25T14:15:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-25T13:56:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-27T07:26:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-24T09:26:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-24T09:24:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-22T08:24:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"831ca413-70bf-467d-a932-0ae75d07d523","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":58738442,"name":"Health sciences/Diseases"},{"id":58738443,"name":"Health sciences/Health care"},{"id":58738444,"name":"Health sciences/Medical research"},{"id":58738445,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-04-07T16:01:44+00:00","versionOfRecord":{"articleIdentity":"rs-7920636","link":"https://doi.org/10.1038/s41598-026-45165-1","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-04-04 15:58:34","publishedOnDateReadable":"April 4th, 2026"},"versionCreatedAt":"2025-12-02 13:41:24","video":"","vorDoi":"10.1038/s41598-026-45165-1","vorDoiUrl":"https://doi.org/10.1038/s41598-026-45165-1","workflowStages":[]},"version":"v1","identity":"rs-7920636","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7920636","identity":"rs-7920636","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}