Elucidating The Burden of Dual-Sensory Impairment in Community-based Older Individuals in a Multi- Ethnic Society

Elucidating The Burden of Dual-Sensory Impairment in Community-based Older Individuals in a Multi- Ethnic Society | 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 Elucidating The Burden of Dual-Sensory Impairment in Community-based Older Individuals in a Multi- Ethnic Society Isabelle Nooteboom, Eva K. Fenwick, Ryan E. K. Man, Johnny C.M. Wong, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7920823/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Apr, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract We aimed to determine the prevalence, risk factors, patient-centered impact and health-related costs of three types of dual sensory impairment (DSI) in a multi-ethnic older Asian population. In this population-based, cross-sectional study (2017–2022) of 2,048 Asian adults aged ≥ 60 years, vision, hearing and olfactory impairments (VI, HI and OI) were assessed using validated clinical tests. DSI types included: VI + HI, VI + OI, and HI + OI. Age-, sex-, and ethnicity-adjusted prevalence rates (2020 Singapore Census) were calculated. Regression analyses identified associated risk factors, impacts and healthcare costs. Of the 2,048 participants (mean age±standard deviation [SD] 75.7±7; 49.5% female), prevalence rates of VI + OI, VI + HI, OI + HI were 1.0%, 7.3% and 21.7%, respectively. Older age (OR1.22) and multimorbidity (OR3.74) were significantly associated with VI + HI, while older age (OR1.23), males (OR3.62), living alone (OR2.37) and current smoking (OR2.51) were associated with higher odds of OI + HI. VI + HI was associated with lower HRQoL-scores (β: -0.025), while VI + HI (OR2.34) and OI + HI (OR2.05) were associated with lower IADL status. Significantly higher healthcare costs (2-fold) were found for OI + HI compared to those without. DSI, particularly OI + HI, is relatively prevalent in older Singaporean adults. Early identification and targeted screening of at-risk groups may mitigate adverse outcomes and healthcare cost, given the global ageing population. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors DSI Epidemiology Risk factors Determinants Patient Centered Impact Health Care costs Productivity costs Figures Figure 1 INTRODUCTION Global projections estimate that by 2050, the proportion of people aged ≥ 60 years will nearly double, with the largest increase estimated to be in Eastern and Southeast Asia. 1 Ageing is associated with declines in sensory acuity, 2–4 and the proportion of individuals with any sensory impairment will also approximately double by 2050. 5 , 6 Dual sensory impairment (DSI, often defined as concurrent vision impairment [VI] and hearing impairment [HI]), is also highly prevalent in older adults 7 , 8 and has been shown to have more deleterious consequences than single sensory loss. 9 , 10 However, in recent years, there is growing interest in age-related olfactory impairment [OI], as it has been found to be a strong predictor of several adverse health outcomes, including cognitive impairment. 11 , 12 In this paper, we define DSI as any combination of two sensory impairments of either VI, HI or OI. Large population-based studies on DSI (without OI in their definition) have shown prevalence rates ranging from 0.9% to 49.7%, 13 with determinants such as smoking and cardiovascular disease (CVD); 14 associated with health impact factors such as lower quality of life (QoL) scores; 15 and increased health care costs. 16 However, most were conducted in Western Europe or North America 7 with only a minority of studies conducted in Asian populations, meaning findings to date may not be generalized to the Asian population due to cultural, environmental, and life-style differences. In addition, many studies have assessed DSI via self-report, 17–24 or unvalidated questionnaires with 1–2 items, 7 which limit the accuracy of these results. Moreover, studies on the prevalence and determinants of DSI that included OI in their definition remain scarce despite the high prevalence of OI (~ 50%) among older adults and its substantial health-related burden, such as decreased QoL. 25 26, 27 Similarly, studies on the economic burden of DSI are lacking with only a handful of population-based studies reporting on the association between increased healthcare spending and DSI (without OI in their definition), and the cost studies performed in Asia have used self-report rather than objectively assessed sensory impairment (i.e. VI, HI or OI). 16 , 28 , 29 These are important knowledge gaps given the increasing prevalence and adverse impact of DSI against the backdrop of a rapidly ageing global population. In this paper, with the inclusion of OI as part of DSI definition, we report on the prevalence; risk determinants; associated patient-centred impact and economic burden of three DSI combinations (VI + HI; HI + OI or OI + VI) in a large, multi-ethnic community-dwelling population of Singaporean adults aged ≥ 60 years participating in the PopulatION Health and Eye Disease Profile in Elderly Singaporeans ( PIONEER) study. We hypothesized considerable but differing prevalence estimates of DSI combinations; and that several sociodemographic (e.g., age and sex), lifestyle factors (e.g., smoking) and systemic conditions would be associated with these DSI combinations. We also expect a worse patient centered and economic outcomes in participants with these combinations DSI as opposed to those with no sensory impairment (NSI). Elucidating the burden of various DSI combinations, and the impact of sociodemographic and lifestyle differences amidst disparities in health outcomes across ethnic lines, may help to inform more targeted public health strategies. METHODS Study Design and Population PIONEER is a population-based study of 2643 community-dwelling Chinese, Malay, and Indian adults aged ≥ 60 years living in Singapore. The baseline visit was conducted between 2017 and 2022, and a detailed methodology has been published previously ( Supplementary Materials 1 ). 30 Of the 2643 participants, 595 were excluded for our analysis due to age (aged less than 60 years n = 2), other races (n = 5), and missing data on presenting visual acuity (n = 13), Sniffin’ Sticks test (n = 536), or hearing assessment (n = 383), resulting in 2048 participants for this study ( Supplementary Fig. 1 ). For the prevalence estimates, all 2048 participants were included. However, for the determinant and impact analyses, an additional 995 participants were excluded due to having single sensory impairment (SSI; n = 816) or multiple sensory impairment (MSI; n = 179), resulting in 1053 participants for these specific analyses. All study procedures were approved by the SingHealth Centralized Institutional Review Board (CIRB, Reference #2016/3089), and adhere to the principles of the Declaration of Helsinki. Written consent was obtained from all participants. Assessment and Definitions of Vision, Hearing, Olfactory Impairments Presenting distance visual acuity (PDVA) was measured monocularly using a logMAR number chart (Lighthouse International, Distance VA Number Chart) at 4 m with participants wearing their habitual optical correction (if any), under standard photopic conditions (85 cd/m 2 ). If the participants were unable to read the largest line of letters, the chart was moved to 2 m. However, if they were still unable to read any letters at 2 m, finger counting, hand movements and the ability of the eye to perceive light with a pen torch were assessed. Presence of VI was defined as PDVA worse than 20/40 (> 0.3 logMAR) in the better eye in accordance with the World Health Organization (WHO) criteria for visual impairment. 31 We also utilized VI in the worse eye in supplementary analyses ( Supplementary Materials 2 ). Hearing for each ear was quantified by a trained study coordinator using a portable pure tone audiometer (SHOEBOX Audiometer - Clearwater Clinical Limited, Ottawa, Canada) in a quiet room with background noise monitoring. Air-conduction thresholds at 500 Hz, 1000 Hz, 2000 Hz and 4000 Hz were recorded, and pure tone average (PTA) was calculated. HI was defined by PTA > 25 dB in the better ear in accordance to the WHO criteria for HI. 32 We also conducted sensitivity analyses using HI definition in the worse ear in Supplementary Materials 2 . The 16-item identification segment of the Sniffin’ Sticks test battery was used to determine olfactory function. Odour impregnated felt pen tips were presented at intervals of 30 seconds of each test-odor presentation, and participants were tasked to select the correct odorant descriptor from four multiple choice questions. The number of correct answers were summed in an overall score, with the maximum score being 16. 33 Any OI was defined as a score of < 11 based on updated cut-points published by Hummel and colleagues. 34 , 35 Any DSI was defined as any impairment of two senses as described above i.e., HI + VI, HI + OI, or VI + OI. NSI was defined as the absence of VI, HI and OI. Assessment of Health-related Outcomes Trained research staff conducted face-to-face interviews to collect the following questionnaire data and performed standardized clinical examinations for the clinical data. Health-Related Quality of Life (HR-QoL) was assessed using the EuroQoL5-Dimensions Health States (EQ-5D-5L). 36 The EQ-5D-5L assesses 5 different health states: mobility, self-care, usual activity pain/discomfort and anxiety/depression. A utility index ranging from 1 (perfect health) to -0.59 (worse health) was calculated for all participants using established UK EQ-5D tariffs. 37 Life-space mobility was quantified using the Life-Space Questionnaire, 38 which was adapted for use in a Singaporean context. The 7-item questionnaire is designed to determine the life-space accessed (e.g., house, neighborhood, country) within the past 3 days of the participant. Each item is scored 1 with ‘yes’, and 0 with ‘no’. The maximum score is 7, corresponding with the largest life space mobility possible. Low life-space mobility was defined as a score of < 5 (median). Presence of low Instrumental Activities of Daily Living (IADL) was determined using the 8-item Lawton IADL scale. 39 Items were recoded to reflect increasing independence of the individual, with a score of 0 being the least independent and 2 being the most independent. ‘Dependent, low function’ is defined as a total Lawton score of < 16. Falls and fall frequency over the past 12 months were quantified using an in-house questionnaire; and hospitalization frequency and duration over the past 6 months were assessed using the modified healthcare services expenditure module. 40 This module was also used to assess direct healthcare expenditure , comprising hospitalization and emergency department visit costs over the past 6 months, and mental health and outpatient service utilization over the past 3 months, extrapolated to annual healthcare expenditure. Dual Energy X-Ray Absorptiometry (DXA; Discovery-W. Hologic Inc. Bedford-MA) was used to measure whole and regional body compositions, including fat and muscle mass, and bone mineral density (BMD). Based on the Asian Working Group for Sarcopenia (2019) recommended cut-offs, sarcopenia was defined as having low appendicular muscle mass (men < 7 kg/m 2 , women < 5.4 kg/m 2 ) in the presence of either low grip strength (men < 28 kg, women < 18 kg) or low gait speed (-1 SD), osteopenia (-1 ≥ T-score >-2.5 SD), and osteoporosis (T-score ≤ -2.5SD). 42 Therefore, osteoporosis was defined a low BMD (T-score, ≤ −2.5) in any of the following sites: hip, femoral, neck, and lumbar spine. Frailty was defined according to the modified Fried criteria 43 as having 3 or more of the following conditions: shrinkage (Body Mass Index [BMI] < 18.5), low gait speed (< 1.0m/s assessed using a 4 m gait speed test), low grip strength (men < 28 kg, women < 18 kg quantified using a digital hand dynamometer (JAMAR Plus+, JLW instruments, Illinois, USA)), exhaustion (score of < 10 for three questions from the vitality domain of the 12-item Short-form survey SF-12), low physical activity levels (defined as the sex-specific lowest quintile of total self-reported duration spent carrying out moderate and vigorous activity (e.g., gardening, brisk walking, dancing, jogging). 43 Assessment of Covariates Participants’ sociodemographic details, including age, sex, ethnicity, socioeconomic status (SES); self-reported medical history (presence of diabetes, hypertension, dyslipidemia, cardiovascular disease, chronic kidney disease; number of medications); and lifestyle factors (smoking status and frequency of alcohol consumption) were collected via an in-house questionnaire. Low SES was defined as having primary or lower education and a monthly household income below $ 2000 SGD. 44 Clinical covariates were collected via standardized clinical examination: weight and height were measured using a wall-mounted, adjustable measuring scale and a calibrated scientific weight scale, respectively. BMI was calculated as weight in kilograms divided by height in meters squared (Weight 45 /Height[m] 2 ). BMI was categorized as underweight (< 18.5), normal (18.5 ≤ BMI 27.5) according to Asian cut-offs. 46 Systolic and diastolic blood pressure was measured twice using an automated blood pressure (Dinamap Pro Series DP110X-RW; GE Medical Systems Information Technologies, Inc), with a third reading taken if the two previous systolic or diastolic readings differed by more than 10- or 5-mm Hg, respectively. The mean of the closest two readings was used in analyses. Hypertension was defined as SBP ≥ 140mmHg, DBP ≥ 90mmHg, self-reported use of anti-hypertensive medications, or self-reported history of physician-diagnosed hypertension. 44 Blood samples were collected for hemoglobin A1c (HbA1c); random glucose; total, high-density lipoprotein and low-density lipoprotein cholesterol; and triglyceride levels. Diabetes was defined as random glucose ≥ 11.1mmol/L, HbA1c ≥ 6.5%, self-reported use of diabetic medication or reported history of physician-diagnosed diabetes. 44 Dyslipidemia was defined as total cholesterol ≥ 5.2 mmol/L, LDL cholesterol ≥ 3.4 mmol/L, triglycerides ≥ 1.7 mmol/L or use of anti-cholesterol medication. 44 Polypharmacy was considered present if the patient was taking 5 or more medications (excluding short-term medication, e.g., pain; supplements; or vitamins). Chronic kidney disease (CKD) was defined as an estimated glomerular filtration rate (eGFR) < 60mL/min/1.73m 2 47 and CVD was defined as having a history of angina, stroke, or heart attack. Lastly, multimorbidity was defined as having ≥ 3 of the following systemic conditions: diabetes, hypertension, dyslipidemia, CVD, CKD. Statistical Analyses Descriptive statistics were performed to characterize the study population. Continuous variables were described with means and SDs. Categorical variables were reported using numbers and percentages. As we oversampled minority races, females, and older participants, the overall, age-, sex-, and ethnicity-stratified prevalence rates for DSI combinations were determined by weighting individuals according to their sampling probabilities and standardizing to Singapore’s 2020 population census. To identify the determinants of the three types of DSI, we performed logistic regression analysis, including pre-defined determinants such as age, sex, ethnicity, low SES, living alone, BMI category, smoking status, alcohol consumption frequency, polypharmacy and multimorbidity into the model, followed by a dominance analysis to assess the individual contribution of each determinant to the overall model. The outcome of interest was participants with a particular type of DSI (e.g., VI + HI), with the reference group being those with NSI. To determine the associations between DSI and patient-centered outcomes, we performed multivariable linear regression analysis on continuous outcomes (i.e., Health-Related Quality of Life (EQ-5D-5L) and life-space mobility) and multivariable logistic regression analysis on binary outcomes (i.e., low IADL status, falls, hospitalizations, osteoporosis, frailty and sarcopenia). The reference group for the multivariable regression was NSI. We utilized two-part models to determine the associations between DSI and health care costs. The first model consists of logistic regression models and the second model consists of gamma generalized linear models with log link function. All analyseswere adjusted for potential confounders, such as age, sex, ethnicity, low SES, living alone, smoking status, polypharmacy and multimorbidity. All statistical analyses were performed using R version 4.3.1. A p-value (2-sided) < 0.05 was considered statistically significant. Additional sensitivity analyses using worse eye/ear definitions for DSI were performed and provided in Supplementary Materials 2. RESULTS The any DSI group (n = 711) was on average 75.7 ±7.8 years old, of which 352 (49.5%) were female, and 348 (48.9%), 195 (27.4%), 168 (23.6%) were Chinese, Malays and Indians, respectively. A descriptive summary of the demographic, systemic, socioeconomic characteristics and health-related outcomes stratified by DSI status is provided in Table 1 . Table 1 Demographic, systemic, and socioeconomic characteristics of participants in the PIONEER study, stratified by DSI status (NSI, DSI) Characteristics NSI (n = 342) DSI 1 (n = 711) Overall (N = 1053) Mean (SD) or n (%) Age (year) 66.7 (5.4) 75.7 (7.8) 72.7 (8.3) Female sex 238 (69.6) 352 (49.5) 590 (56.0) Race Chinese 163 (47.7) 348 (48.9) 511 (48.5) Malay 91 (26.6) 195 (27.4) 286 (27.2) Indian 88 (25.7) 168 (23.6) 256 (24.3) Low socioeconomic status 33 (9.6) 129 (18.1) 162 (15.4) Living alone 18 (5.3) 87 (12.2) 105 (10.0) BMI categories Underweight 15 (4.4) 32 (4.5) 47 (4.5) Normal 89 (26.0) 198 (27.8) 287 (27.3) Overweight/Obese 238 (69.6) 479 (67.4) 717 (68.1) Smoking status Never smoked or past smoker 319 (93.3) 615 (86.5) 934 (88.7) Current smoker 18 (5.3) 70 (9.8) 88 (8.4) Alcohol frequency None 282 (82.5) 591 (83.1) 873 (82.9) ≤ 4 days/week 24 (7.0) 54 (7.6) 78 (7.4) > 4 days/week 5 (1.5) 20 (2.8) 25 (2.4) Polypharmacy 52 (15.2) 171 (24.1) 223 (21.2) Any systemic condition 327 (95.6) 698 (98.2) 1025 (97.3) Systemic conditions Diabetes 87 (25.4) 272 (38.3) 359 (34.1) Hypertension 271 (79.2) 620 (87.2) 891 (84.6) Dyslipidaemia 290 (84.8) 564 (79.3) 854 (81.1) CVD 42 (12.3) 138 (19.4) 180 (17.1) CKD 26 (7.6) 153 (21.5) 179 (17.0) Multimorbidity 104 (30.4) 317 (44.6) 421 (40.0) 1. DSI subjects consists of 15 (2.1%) VI + OI subjects, 173 (24.3%) VI + HI subjects, and 523 (73.6%) OI + HI subjects. BMI: Body Mass Index; CKD: Chronic Kidney Disease; CVD: Cardiovascular Disease; DSI: Dual Sensory Impairment; HI: Hearing Impairment; NSI: No Sensory Impairment; OI: Olfactory Impairment; SD: Standard Deviation; VI: Visual Impairment. The crude prevalence of VI + OI, VI + HI, OI + HI was 0.7%, 8.4% and 25.5%, respectively; and the related census-adjusted prevalence was 1.0%, 7.3% and 21.7%, respectively (Tables 2 ). Overall, the weighted prevalence of DSI combinations (except VI + OI) increased with age (p-trend < 0.05, Tables 2 ). Sex-stratified results revealed no difference in the prevalence between males and females in VI + OI group, while females had higher prevalence rates of VI + HI than males, both overall (9.4% in females vs 5% in males) and across age groups, and males had higher prevalence rates of OI + HI than females, both overall (28.8% in males vs 15.3% in females) and across age groups. Ethnicity stratified analyses showed no difference in the prevalence of DSI combinations across the three ethnic groups sampled. Table 2 Weighted prevalence of DSI, stratified by age, sex and ethnicity in the PIONEER study. Age group All (N = 2048) Sex Ethnicity Male (N = 919) Female (N = 1129) Chinese (N = 992) Malay (N = 582) Indian (N = 474) n Weighted, % (95% CI) n Weighted, % (95% CI) n Weighted, % (95% CI) n Weighted, % (95% CI) n Weighted, % (95% CI) n Weighted, % (95% CI) VI + OI 60–69 5 1.0 (0.3, 2.3) 4 1.5 (0.3, 4.0) 1 0.4 (0.0, 2.5) 4 1.1 (0.3, 2.8) 1 0.4 (0.0, 2.4) 0 - 70–79 6 0.9 (0.3, 2.2) 0 - 6 1.7 (0.5, 4.1) 4 1.0 (0.3, 2.5) 0 - 2 1.3 (0.2, 4.5) ≥ 80 4 1.1 (0.3, 2.9) 2 1.5 (0.2, 5.6) 2 0.9 (0.1, 3.2) 4 1.3 (0.3, 3.4) 0 - 0 - P-trend - - - - - - Total 15 1.0 (0.5, 1.8) 6 1.1 (0.3, 2.5) 9 0.9 (0.3, 1.9) 12 1.1 (0.5, 2.0) 1 0.3 (0.0, 1.6) 2 0.3 (0.0, 1.2) VI + HI 60–69 43 4.7 (3.1, 6.9) 15 3.6 (1.7, 6.6) 28 5.8 (3.3, 9.3) 16 4.5 (2.6, 7.2) 17 6.3 (3.7, 9.9) 10 5.1 (2.5, 9.2) 70–79 65 9.3 (6.9, 12.2) 17 5.9 (3.0, 10.2) 48 12.2 (8.7, 16.6) 35 9.3 (6.5, 12.7) 18 10.3 (6.3, 15.7) 12 7.9 (4.1, 13.5) ≥ 80 65 13.9 (10.0, 18.6) 23 9.7 (5.5, 15.6) 42 16.5 (10.8, 23.5) 34 14.3 (9.8, 19.7) 13 9.6 (4.9, 16.5) 18 13.9 (8.3, 21.3) P-trend P-trend < 0.001 P-trend = 0.011 P-trend < 0.001 P-trend < 0.001 P-trend = 0.135 P-trend = 0.006 Total 173 7.3 (6.0, 8.8) 55 5.0 (3.4, 7.0) 118 9.4 (7.4, 11.8) 85 7.3 (5.8, 9.1) 48 7.6 (5.5, 10.2) 40 6.9 (4.7, 9.7) OI + HI 60–69 123 14.9 (12.1, 18.2) 86 23.7 (18.6, 29.4) 37 6.4 (3.9, 9.9) 53 14.7 (11.3, 18.7) 39 15.6 (11.4, 20.7) 31 16.6 (11.6, 22.7) 70–79 198 27.3 (23.4, 31.5) 109 35.1 (28.5, 42.2) 89 20.6 (16.1, 25.7) 94 26.6 (22.2, 31.5) 57 31.4 (24.7, 38.8) 47 31.6 (24.3, 39.6) ≥ 80 202 37.5 (32.1, 43.3) 103 40.1 (32.4, 48.1) 99 35.9 (28.5, 44.0) 104 37.5 (31.3, 44.1) 50 37.5 (28.7, 47.0) 48 38.0 (29.6, 46.9) P-trend P-trend < 0.001 P-trend < 0.001 P-trend < 0.001 P-trend < 0.001 P-trend < 0.001 P-trend < 0.001 Total 523 21.7 (19.5, 24.0) 298 28.8 (25.1, 32.8) 225 15.3 (13.0, 17.9) 251 21.6 (19.0, 24.3) 146 21.8 (18.4, 25.5) 126 23.1 (19.2, 27.3) Weighted prevalences are calculated with sampling weights specific to each age group, sex and ethnicity to adjust for oversampling and post-stratification weights to align to the population distribution based on the 2020 Singapore Census. P-trend will not be computed for counts less than 5 in any age group or if the total count is less than 20. CI: Confidence Interval; DSI: Dual Sensory Impairment; HI: Hearing Impairment; OI: Olfactory Impairment; VI: Visual Impairment. As stated above, only 1053 participants (771 with any DSI and 342 with NSI) were included in the determinants, impact and costs analyses. Moreover, because of the low number of individuals with VI + OI, this DSI combination was not included in risk determinant analysis. In adjusted models (Tables 3 ) older age was significantly associated with VI + HI: OR 1.22 [95%CI: 1.16, 1.29] and OI + HI: OR 1.23 [95%CI: 1.19, 1.28]. Dominance analysis showed that age contributed 70.4% and 70.8% of the variance for VI + HI and OI + HI, respectively. Multimorbidity was associated with increased odds of VI + HI (OR 3.74 [95%CI 1.86, 7.69]), and contributed 10.8% of the variance, while obesity was associated with decreased odds of VI + HI (OR 0.19 [95%CI: 0.19, 0.77]) and contributed 2.5% of the variance. Table 3 A. Factors associated with DSI (VI + HI) Risk factor Model Dominance analysis OR (95% CI) P-value Contribution 1 (%) Rank 2 Age (year) 1.22 (1.16, 1.29) < 0.001 70.4 1 Sex 0.1 9 Female Reference NA Male 0.89 (0.44, 1.77) 0.742 Race 0.7 7 Chinese Reference NA Malay 1.20 (0.57, 2.54) 0.628 Indian 0.89 (0.41, 1.88) 0.752 Low socioeconomic status 13.4 2 No Reference NA Yes 1.73 (0.75, 3.95) 0.195 Living alone 2.0 5 No Reference NA Yes 1.84 (0.62, 5.24) 0.260 BMI categories 2.5 4 Normal Reference NA Underweight 0.88 (0.18, 3.38) 0.866 Overweight/Obese 0.38 (0.19, 0.77) 0.007 Smoking status 0.8 6 Never or past smoker Reference NA Current smoker 2.81 (0.85, 9.08) 0.085 Alcohol frequency -1.4 10 None Reference NA ≤ 4 days/week 1.13 (0.37, 3.14) 0.814 > 4 days/week 1.44 (0.17, 9.64) 0.711 Polypharmacy 0.6 8 No Reference NA Yes 0.48 (0.20, 1.08) 0.081 Multimorbidity 10.8 3 No Reference NA Yes 3.74 (1.86, 7.69) < 0.001 1: Contribution is the standardized dominance statistics in the dominance analysis from the model. 2. The ranks of each predictor are ranked from predictors with the greatest contribution to the least. Low Socioeconomic Status: Having primary or lower education and individual monthly income < SGD2000; BMI categories: BMI < 18.5 kg/m 2 as underweight, BMI between 18.5 and 22.9 kg/m 2 (inclusive) as normal, BMI ≥ 23 kg/m 2 as overweight/obese; Polypharmacy: Taking ≥ 5 medications (exclude supplements or vitamins); Multimorbidity: Having more than or equal to 3 systemic conditions (diabetes, hypertension, dyslipidemia, CVD, CKD). BMI: Body Mass Index; CI: Confidence Interval; CKD: Chronic Kidney Disease; CVD: Cardiovascular Disease; DSI: Dual Sensory Impairment; HI: Hearing Impairment; OR: Odds Ratio; VI: Visual Impairment. Table 3 B . Factors associated with DSI (OI + HI) Risk factor Model Dominance analysis OR (95% CI) P-value Contribution 1 (%) Rank 2 Age (year) 1.23 (1.19, 1.28) < 0.001 70.8 1 Sex 13.9 2 Female Reference NA Male 3.62 (2.26, 5.88) < 0.001 Race 0.3 10 Chinese Reference NA Malay 1.10 (0.64, 1.87) 0.730 Indian 0.94 (0.54, 1.63) 0.823 Low socioeconomic status 3.4 3 No Reference NA Yes 1.09 (0.57, 2.10) 0.791 Living alone 2.7 6 No Reference NA Yes 2.37 (1.09, 5.40) 0.033 BMI categories 0.3 9 Normal Reference NA Underweight 0.62 (0.19, 1.94) 0.423 Overweight/Obese 1.13 (0.66, 1.92) 0.663 Smoking status 2.9 5 Never or past smoker Reference NA Current smoker 2.51 (1.21, 5.40) 0.015 Alcohol frequency 1.4 7 None Reference NA ≤ 4 days/week 0.93 (0.45, 1.93) 0.842 > 4 days/week 1.64 (0.46, 6.94) 0.469 Polypharmacy 1.1 8 No Reference NA Yes 0.84 (0.45, 1.55) 0.578 Multimorbidity 3.3 4 No Reference NA Yes 1.11 (0.65, 1.88) 0.701 1: Contribution is the standardized dominance statistics in the dominance analysis from the model. 2. The ranks of each predictor are ranked from predictors with the greatest contribution to the least. Low Socioeconomic Status: Having primary or lower education and individual monthly income < SGD2000; BMI categories: BMI < 18.5 kg/m 2 as underweight, BMI between 18.5 and 22.9 kg/m 2 (inclusive) as normal, BMI ≥ 23 kg/m 2 as overweight/obese; Polypharmacy: Taking ≥ 5 medications (exclude supplements or vitamins); Multimorbidity: Having more than or equal to 3 systemic conditions (diabetes, hypertension, dyslipidemia, CVD, CKD) BMI: Body Mass Index; CI: Confidence Interval; CKD: Chronic Kidney Disease; CVD: Cardiovascular Disease; DSI: Dual Sensory Impairment; HI: Hearing Impairment; OI: Olfactory Impairment; OR: Odds Ratio. Male sex (OR 3.62 [95% CI: 2.26, 5.88]), current smoking (OR 2.51 [95% CI: 1.21, 5.40]), and living alone (OR 2.37 [95%CI 1.09, 5.40]) were associated with increased odds of OI + HI and contributed 13.9%, 2.9% and 2.7% of the variance, respectively. In multivariable regression models, VI + HI was significantly associated with lower HRQoL scores (B: -0.025 [95%CI -0.049, -0.001]). VI + HI and OI + HI were significantly associated with lower IADL status, (OR: 2.34 [95% CI 1.14, 4.81]) and (OR: 2.05 [95% CI1.12, 3.81]), respectively. We found no significant associations between DSI combinations and life space mobility, falls, hospitalizations, osteoporosis, frailty, and sarcopenia (Table 4 ). Table 4 Associations between DSI and patient-reported outcomes PRO Exposure Estimate 1 (95% CI) P-value Overall marginal effect (95% CI) Change (%) EQ-5D-5L NSI Reference NA NA NA VI + OI 0.004 (-0.057, 0.066) 0.888 0.004 (-0.057, 0.066) 0.49 VI + HI -0.025 (-0.049, -0.001) 0.045 -0.025 (-0.049, -0.001) -2.75 OI + HI 0.005 (-0.014, 0.024) 0.605 0.005 (-0.014, 0.024) 0.54 Life space mobility NSI Reference NA NA NA VI + OI -0.364 (-0.858, 0.130) 0.148 -0.364 (-0.858, 0.129) -7.93 VI + HI -0.155 (-0.350, 0.040) 0.120 -0.155 (-0.350, 0.040) -3.37 OI + HI -0.118 (-0.268, 0.032) 0.123 -0.118 (-0.268, 0.032) -2.57 Low IADL status NSI Reference NA NA NA VI + OI OR: 0.92 (0.04, 6.38) 0.944 -0.01 (-0.21, 0.20) -7.21 VI + HI OR: 2.34 (1.14, 4.81) 0.020 0.10 (0.01, 0.18) 109.08 OI + HI OR: 2.05 (1.12, 3.81) 0.022 0.08 (0.01, 0.15) 87.02 Falls NSI Reference NA NA NA VI + OI OR: 0.60 (0.09, 2.67) 0.545 -0.07 (-0.28, 0.13) -34.83 VI + HI OR: 0.55 (0.27, 1.06) 0.084 -0.08 (-0.17, 0.00) -39.76 OI + HI OR: 0.83 (0.50, 1.37) 0.476 -0.03 (-0.11, 0.05) -13.88 Hospitalisations NSI Reference NA NA NA VI + OI OR: 1.88 (0.09, 12.92) 0.583 0.06 (-0.18, 0.29) 82.23 VI + HI OR: 0.76 (0.26, 2.03) 0.597 -0.02 (-0.08, 0.05) -23.38 OI + HI OR: 0.79 (0.36, 1.72) 0.556 -0.02 (-0.07, 0.04) -20.17 Osteoporosis NSI Reference NA NA NA VI + OI OR: 0.48 (0.07, 2.01) 0.370 -0.11 (-0.32, 0.09) -42.49 VI + HI OR: 1.33 (0.75, 2.31) 0.322 0.06 (-0.06, 0.17) 20.43 OI + HI OR: 1.01 (0.64, 1.60) 0.960 0.00 (-0.08, 0.09) 0.81 Frailty NSI Reference NA NA NA VI + OI OR: 2.73 (0.37, 13.02) 0.249 0.11 (-0.12, 0.34) 120.84 VI + HI OR: 1.60 (0.68, 3.72) 0.275 0.04 (-0.04, 0.12) 47.97 OI + HI OR: 1.50 (0.75, 3.07) 0.260 0.04 (-0.02, 0.10) 40.12 Sarcopenia NSI Reference NA NA NA VI + OI OR: 1.56 (0.40, 6.27) 0.521 0.09 (-0.19, 0.38) 25.70 VI + HI OR: 1.17 (0.67, 2.01) 0.584 0.03 (-0.08, 0.15) 8.85 OI + HI OR: 1.23 (0.80, 1.87) 0.347 0.04 (-0.05, 0.13) 11.75 1. For PROs EQ-5D-5L, and life space mobility, the estimates are coefficients derived from linear regression models. The remaining PROs are odds ratios (OR) derived from logistic regression models. All models are adjusted for age, sex, ethnicity, low socioeconomic status, living alone, smoking status, polypharmacy and multimorbidity. CI: Confidence Interval; DSI: Dual Sensory Impairment; EQ-5D-5L: EuroQoL 5-dimension 5-level; HI: Hearing Impairment; IADL: Instrumental Activities of Daily Living; NSI: No sensory impairment; OI: Olfactory Impairment; OR: Odds Ratio; PRO: Patient-Reported Outcome; VI: Visual Impairment Associations between DSI and those with incurred health care costs were significant for the OI + HI group, which showed a trend towards substantially higher cost ratios of 2.09 [95% CI: 0.82, 5.36] compared to NSI (Table 5 ). Table 5 Associations between DSI and costs using two-parts model. Outcome Exposure First part Second part Overall marginal effect* (95% CI) OR (95% CI) P-value Cost Ratio (95% CI) P-value Healthcare cost (in SGD) Robust Reference NA Reference NA NA VI + OI 0.67 (0.14, 2.56) 0.581 0.39 (0.05, 45.76) 0.508 -197.81 (-488.59, 92.98) VI + HI 0.72 (0.41, 1.23) 0.234 2.49 (0.82, 8.73) 0.106 293.76 (-311.81, 899.34) OI + HI 0.74 (0.49, 1.12) 0.155 2.09 (0.82, 5.36) 0.063 210.91 (-115.96, 537.77) In the two-parts model, the first part results were odds ratios from logistic regression models and the second part results were cost ratios (exponentiated coefficients) from gamma generalised linear models with a log-link function for healthcare cost. All models are adjusted for age, sex, ethnicity, low socioeconomic status, living alone, smoking status, polypharmacy and multimorbidity. * The costs were shown in SGD. Based on the exchange rate of 1 SGD to 0.74515 USD on 31 Dec 2022, the USD equivalent costs were − 147.40, 218.90 and 157.16 for VI + OI, VI + HI and OI + HI, respectively. CI: Confidence Interval; DSI: Dual Sensory Impairment; HI: Hearing Impairment; NSI: No Sensory Impairment; OI: Olfactory Impairment; OR: Odds Ratio; PRO: Patient-Reported Outcome; VI: Visual Impairment Using worst eye/worst ear definitions ( Supplementary Materials 2) , census-adjusted prevalence rates were slightly higher as expected: census-adjusted prevalence of VI + OI, VI + HI, and OI + HI was 2.0%, 22.0% and 15.0%, respectively. Further analyses of risk factors showed older age and smoking were associated with VI + HI, while age, male sex and smoking were associated with OI + HI. Surprisingly, except for VI + OI that was associated with lower odds of osteoporosis (OR 0.112 [CI: 0.006, 0.600]), no significant associations between DSI categories and any other patient centred outcomes was observed. DISCUSSION In our nationally representative sample of older Singaporean adults, we found for the first time that of the three DSI combinations, OI + HI was most prevalent, in over one in five participants. Several sociodemographic (older age, male sex, living alone), lifestyle (smoking), and health-related factors (multimorbidity) were associated with the DSI combinations assessed, with older age being the major driving factor overall. Several DSI combinations were associated with lower HR-QoL scores and a low IADL status. Only those with OI + HI incurred a substantially higher healthcare cost than those without. Our findings demonstrate the importance of screening for DSI combinations, particularly OI + HI, in older male adults and those who smoke and live alone for early detection and timely management via relevant intervention strategies such as hearing aids, ophthalmic aids or possible olfactory training. Longitudinal studies are needed to determine the predictors of incident DSI combinations and gain a deeper understanding of underlying mechanisms. As our study is the first population-based study to report on the prevalence of “OI+” DSI combinations, it is difficult to compare results pertaining to such combinations to existing literature. However, the VI + HI prevalence rate of 7.3% is comparable to previously reported VI + HI prevalence rates in Singaporean studies. For example, Phua and colleagues reported a self-reported DSI prevalence rate of 12.8% 48 in a large population-based study of 4077 participants, while Tareque and associates found a prevalence rate of 11.6% 49 in their large population-based study of 3452 subjects (self-reported VI and HI). Elsewhere in Asia, a small Malaysian study of 229 community-dwelling subjects reported a prevalence rate of 8.3% 50 for VI + HI (objectively assessed HI and VI), while two larger population-based studies of older adults in Malaysia (objectively assessed HI and VI) 51 and Japan 19 (self-reported VI and HI) reported prevalence rates of 10.5% and 11.4%, respectively. These slight inconsistencies may be explained by different methods of sensory assessment (e.g., self-report vs objective measurement) and varying definitions of VI and HI (self-reported vs objectively assessed), different characteristics of participants (e.g., older age, more comorbidities), and different access to health care facilities across countries (e.g., rural vs. urban areas). Our finding that OI + HI was the most prevalent combination of DSI compared to VI + HI or VI + OI in Asian older adults, could be attributed to OI and HI being closely related senses. Studies have demonstrated that conductive smell and hearing disorders are often comorbid, such as chronic rhinosinusitis and otitis media. 52 Furthermore, both these senses are often the most vulnerable to a wide range of chemcial and auditory environmental pollutants/damage, and have limited capacity for regeneration, particularly among older adults. 53 The fact that OI + HI is the most prevalent DSI combination in our study participants highlights the need for community-based initiatives to screen for OI-related DSI in at-risk older adult populations. It is noteworthy that < 1% of our population were using hearing aids. While vision may be considered more vital to patients, and thus patients are more likely to either undergo corrective surgery or wear glasses to help them correct their VI, this may be less so for HI, and even less so for OI. There may also be less surgically correctable diseases for HI and OI compared with VI, meaning that prevention may be more important than cure. Similar to previous studies 54 – 56 that have reported older age as a risk factor of DSI, the present study confirmed age as a major determinant of three combination DSI. The presence of DSI in older individuals is likely due to age-related anatomical and physiological changes of the sensory systems. 57 VI among older adults can, for example, can be explained by pupillary miosis; and increased rates of cataract 4 and age-related macular degeneration; 58 HI may be due to degeneration of the neural elements, metabolic changes, and stiffening of membranes in the inner ear, 59 and OI caused by head trauma, exposure to environmental pollutants and chemicals, and age related reductions in the number of olfactory receptor cells, cell regeneration and structural and functional changes in the olfactory system. 60 , 61 Other studies have also reported the association of DSI and male sex. 23 , 62 We found that male sex was significantly associated with over a 3 to 4-fold increased odds of OI + HI, similar to a finding where male sex was reported as a risk factor for HI 63 and OI. 64 This may be because men are more likely to work in environments with harmful noise exposure often associated with hearing loss. 65 Moreover, men may have higher exposure to industrial chemicals (including cadmium, chromium, nickel, acrylate, styrene, toluene, formaldehyde, etc.) which are known to be both olfactotoxic and ototoxic. 66 , 67 Living alone has also been identified by previous studies as a risk factor for DSI, 68 corroborating our findings of an increased likelihood of OI + HI in those living alone. Importantly, being a current smoker was significantly associated with almost a threefold increased odds of OI + HI, with similar results being shown in previous studies. 69 These findings highlight the need for targeted messaging about the negative impact of smoking on sensory health. Next, multimorbidity showed an almost 4-fold increased odds for VI + HI, suggesting the need for further investigation on potential underpinning mechanisms. Various neuropathic and angiopathic manifestations consequent to diabetes, dyslipidemia, hypertension, CKD, and CVD might be a related plausible explanation. 70 , 71 For example, individuals with diabetes or CVD may develop microangiopathic changes in the retina and cochlea which may decrease microcirculation to these areas, potentially resulting in sensory impairment. Surprisingly, obesity showed a decreased odds on VI + HI; this might be a case of obesity paradox, again suggesting the need for more research. 72 However, its worth considering if these are simply associations, in which case DSI is a marker of a more general decline but not causally implicated in changes that otherwise lead to the conditions listed - OR - are there plausible causal pathways, such as OI could be related to a shift in food preferences or appetite that can lead to dietary changes that could support the development of chronic nutrition diseases such as diabetes. Like other studies, 68,73 we found an association between VI + HI and a decreased HR-QoL scores. However, other DSI combinations did not show these associations, and this might be because the EQ-5D-5L is a generic HR-QoL questionnaire and may be insensitive at measuring the impact of specific sensory impairments. Hence, other sensory-impairment specific QoL instruments might be more useful in DSI future research. 74 , 75 Moreover, we found that VI + HI and OI + HI was associated with increased odds of low IADL status, like the population-based study of 4214 older adults in Japan by Tomida and associates. 76 This finding is not unexpected given that performing daily activities can be more difficult in the presence of sensory losses. Unlike other studies, 77–79 we found no significant relationship between all DSI combinations and falls and hospitalization. This may be due to the concept of ‘silent-fallers’, as many elderly do not report their falls or may not be able to recall them, resulting in a recall bias in our study. 80 This is complicated by the fact that we were unable to access participant’s medical history and history of falls to verifying participant self-report due to Singapore’s strict data protection laws. Additionally, any DSI combination was not associated with frailty and sarcopenia in our study, a finding which aligns with some studies and not others. 20 , 81 Future research is warranted in this area. Health care cost ratios was significantly higher for OI + HI group, and is in line with the study of Ding and colleagues, which shows that DSI (VI + HI) is associated with higher inpatients and outpatient costs 16 and the study of Deardorff and colleagues (VI + HI). 28 To our knowledge, this is the first DSI study performed in Asia analyzing the economic impact of DSI combinations using objectively assessed sensory impairments, and it clearly shows the stark economic disparity DSI patients are coping with. These numbers imply that policymakers should consider creating specialized subsidy programs to alleviate this economic burden for this growing group of older adults. Strengths of this study include a well-characterized, representative sample of older Singaporeans, the objective assessment of sensory impairments and the inclusion of OI which is rarely included in most DSI studies despite its high burden. We supply additional analysis using the worse eye and ear which allowed us to capture those with unilateral as well as bilateral disease, creating a more accurate picture of the continuum of sensory impairments and thus making our study more inclusive. It also creates the future opportunity to investigate whether those with unilateral DSI vs bilateral DSI might benefit from earlier interventions to either prevent or mitigate their sensory impairments as early as possible. However, several limitations should also be noted. Audiometry was performed using pure tones between 500 and 4000hz, to calculate a pure tone average. Higher frequencies were not tested, thus participants with only high frequency hearing loss were not accounted for in this study. Also, other sensory impairments such as taste and tactile dysfunction were not investigated, which may also have impacted on our health-related outcome analyses. Next, due to the low numbers of the VI + OI group (n = 15), potential risk factors could unfortunately not be presented, and future research with more VI + OI subjects is warranted. Lastly, any causal effects are unknown due to the cross-sectional design of our study. Longitudinal studies are needed to clarify directionality of the associated factors discovered in this study. To elucidate this, a 4.5-year follow-up visit for the PIONEER study (PIONEER II) has started, which will help to understand the changing prevalence of DSI better, determine the directionality of potential risk factors and gain a better understanding of the impact of DSI. In conclusion, our study found for the first time that OI + HI was the most common type of DSI in Asian older adults, which was associated with a series of chronic diseases and also incurred a substantially higher healthcare cost than those without. Older age exerted the largest influence across all types of DSI. Several DSI types were associated with lower HR-QoL scores and a low IADL status. Screening for DSI, particularly OI + HI is warranted for early detection and timely management in this growing group of elderly. Future longitudinal research is needed to further explore the relationships between DSI combinations, its risk factors, and associated dietary and behavioral adaptations and patient-centered and economic burdens. Declarations ACKNOWLEDGEMENTS Funding/Support: Professor Lamoureux is supported by the National Medical Research Council Senior Clinician Scientist Award (CSA-NMRC-CSA-SI #JRNMRR197001 and NMRC-CSA-SI #JRNMRR140601). Role of Funders/Sponsors: The funding sources had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or in the decision to submit the manuscript for publication. Author Contributions : Drs Gupta and Lamoureux had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design : Gupta, Nooteboom and Lamoureux Acquisition, analysis, or interpretation of data : Gupta, Nooteboom, Wong, Fenwick, Man, and Lamoureux. Drafting of manuscript : Gupta, Nooteboom, Fenwick, Man, and Lamoureux. Critical revision of the manuscript for important intellectual content : Gupta, Nooteboom, Fenwick, Man, Wong, Forde, Yeo, Gao, Tan, Yee, Ng, Teo and Lamoureux. Obtained funding: Lamoureux Statistical analysis : Wong Administrative, technical, or material support: Gupta Study Supervision: Gupta, Lamoureux ADDITIONAL INFORMATION Conflict of Interest: All authors have no conflict of interest and there are no competing financial and non-financial interests. Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. All requests will be considered in accordance with institutional and ethical guidelines. References Nations, U. World Population Ageing 2019: Highlights (United Nations, 2019). ST/ESA/SER.A/430 Kaneda, H. et al. Decline in taste and odor discrimination abilities with age, and relationship between gustation and olfaction. Chem. Senses . 25 (3), 331–337 (2000). Gates, G. A., Mills, J. H. & Presbycusis Lancet ; 366 (9491):1111–1120. (2005). Owsley, C. Aging and vision. Vision. Res. 51 (13), 1610–1622 (2011). Bourne, R. R. A. et al. 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Machón, M., Larrañaga, I., Dorronsoro, M., Vrotsou, K. & Vergara, I. Health-related quality of life and associated factors in functionally independent older people. BMC Geriatr. 17 (1), 19 (2017). Summerfield, A. Q. & Barton, G. R. Sensitivity of EQ-5D-3L, HUI2, HUI3, and SF-6D to changes in speech reception and tinnitus associated with cochlear implantation. Qual. Life Res. 28 (5), 1145–1154 (2019). Macedo, A. F. et al. Predictors of problems reported on the EQ-5D-3L dimensions among people with impaired vision in northern Portugal. Health Qual. Life Outcomes . 20 (1), 132 (2022). Tomida, K. et al. Association of dual sensory impairment with changes in life space: A longitudinal study with two-year follow-up. Maturitas 165 , 78–84 (2022). Ogliari, G. et al. Subjective vision and hearing impairment and falls among community-dwelling adults: a prospective study in the Survey of Health, Ageing and Retirement in Europe (SHARE). Eur. Geriatr. Med. 12 (5), 1031–1043 (2021). Gopinath, B., McMahon, C. M., Burlutsky, G. & Mitchell, P. Hearing and vision impairment and the 5-year incidence of falls in older adults. Age Ageing . 45 (3), 409–414 (2016). Zhou, Y. et al. Association Between Sensory Loss and Falls Among Middle-Aged and Older Chinese Population: Cross-Sectional and Longitudinal Analyses. Front. Med. (Lausanne) . 8 , 810159 (2021). Ang, G. C., Low, S. L. & How, C. H. Approach to falls among the elderly in the community. Singap. Med. J. 61 (3), 116–121 (2020). Zhao, Y. et al. Combined Vision and Hearing Impairment is Associated with Frailty in Older Adults: Results from the West China Health and Aging Trend Study. Clin. Interv Aging . 17 , 675–683 (2022). Additional Declarations No competing interests reported. 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08:49:06","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":253081,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7920823/v1/2695686e925bbd1411ee85a5.html"},{"id":95807488,"identity":"cddaf5b7-c7be-419b-9495-f0a4b3cbdca9","added_by":"auto","created_at":"2025-11-13 08:48:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":129459,"visible":true,"origin":"","legend":"\u003cp\u003eSubject flowchart of PIONEER study population\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7920823/v1/2e0ae41d38e33fb4fe293a91.png"},{"id":106343668,"identity":"c796abcc-d11d-460f-9f22-6db89dec100a","added_by":"auto","created_at":"2026-04-07 16:08:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1845581,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7920823/v1/846af87b-4813-4a47-97e8-1bd44f154542.pdf"},{"id":95807587,"identity":"451fdb9c-6893-4796-8059-c5dd34833306","added_by":"auto","created_at":"2025-11-13 08:48:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":278446,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryfileScientificReports.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7920823/v1/ae5308ab3ec72e433842b1dd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Elucidating The Burden of Dual-Sensory Impairment in Community-based Older Individuals in a Multi- Ethnic Society","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eGlobal projections estimate that by 2050, the proportion of people aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years will nearly double, with the largest increase estimated to be in Eastern and Southeast Asia.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Ageing is associated with declines in sensory acuity,\u003csup\u003e2\u0026ndash;4\u003c/sup\u003e and the proportion of individuals with any sensory impairment will also approximately double by 2050.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Dual sensory impairment (DSI, often defined as concurrent vision impairment [VI] and hearing impairment [HI]), is also highly prevalent in older adults\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e and has been shown to have more deleterious consequences than single sensory loss.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e However, in recent years, there is growing interest in age-related olfactory impairment [OI], as it has been found to be a strong predictor of several adverse health outcomes, including cognitive impairment.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e In this paper, we define DSI as any combination of two sensory impairments of either VI, HI or OI.\u003c/p\u003e\u003cp\u003eLarge population-based studies on DSI (without OI in their definition) have shown prevalence rates ranging from 0.9% to 49.7%,\u003csup\u003e13\u003c/sup\u003e with determinants such as smoking and cardiovascular disease (CVD);\u003csup\u003e14\u003c/sup\u003e associated with health impact factors such as lower quality of life (QoL) scores;\u003csup\u003e15\u003c/sup\u003e and increased health care costs.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e However, most were conducted in Western Europe or North America\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e with only a minority of studies conducted in Asian populations, meaning findings to date may not be generalized to the Asian population due to cultural, environmental, and life-style differences. In addition, many studies have assessed DSI via self-report,\u003csup\u003e17\u0026ndash;24\u003c/sup\u003e or unvalidated questionnaires with 1\u0026ndash;2 items,\u003csup\u003e7\u003c/sup\u003e which limit the accuracy of these results. Moreover, studies on the prevalence and determinants of DSI that included OI in their definition remain scarce despite the high prevalence of OI (~\u0026thinsp;50%) among older adults and its substantial health-related burden, such as decreased QoL.\u003csup\u003e25 26,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Similarly, studies on the economic burden of DSI are lacking with only a handful of population-based studies reporting on the association between increased healthcare spending and DSI (without OI in their definition), and the cost studies performed in Asia have used self-report rather than objectively assessed sensory impairment (i.e. VI, HI or OI).\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e These are important knowledge gaps given the increasing prevalence and adverse impact of DSI against the backdrop of a rapidly ageing global population.\u003c/p\u003e\u003cp\u003eIn this paper, with the inclusion of OI as part of DSI definition, we report on the prevalence; risk determinants; associated patient-centred impact and economic burden of three DSI combinations (VI\u0026thinsp;+\u0026thinsp;HI; HI\u0026thinsp;+\u0026thinsp;OI or OI\u0026thinsp;+\u0026thinsp;VI) in a large, multi-ethnic community-dwelling population of Singaporean adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years participating in the PopulatION Health and Eye Disease Profile in Elderly Singaporeans (\u003cb\u003ePIONEER)\u003c/b\u003e study. We hypothesized considerable but differing prevalence estimates of DSI combinations; and that several sociodemographic (e.g., age and sex), lifestyle factors (e.g., smoking) and systemic conditions would be associated with these DSI combinations. We also expect a worse patient centered and economic outcomes in participants with these combinations DSI as opposed to those with no sensory impairment (NSI). Elucidating the burden of various DSI combinations, and the impact of sociodemographic and lifestyle differences amidst disparities in health outcomes across ethnic lines, may help to inform more targeted public health strategies.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Population\u003c/h2\u003e\u003cp\u003ePIONEER is a population-based study of 2643 community-dwelling Chinese, Malay, and Indian adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years living in Singapore. The baseline visit was conducted between 2017 and 2022, and a detailed methodology has been published previously (\u003cb\u003eSupplementary Materials 1\u003c/b\u003e).\u003csup\u003e30\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eOf the 2643 participants, 595 were excluded for our analysis due to age (aged less than 60 years n\u0026thinsp;=\u0026thinsp;2), other races (n\u0026thinsp;=\u0026thinsp;5), and missing data on presenting visual acuity (n\u0026thinsp;=\u0026thinsp;13), Sniffin\u0026rsquo; Sticks test (n\u0026thinsp;=\u0026thinsp;536), or hearing assessment (n\u0026thinsp;=\u0026thinsp;383), resulting in 2048 participants for this study (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e). For the prevalence estimates, all 2048 participants were included. However, for the determinant and impact analyses, an additional 995 participants were excluded due to having single sensory impairment (SSI; n\u0026thinsp;=\u0026thinsp;816) or multiple sensory impairment (MSI; n\u0026thinsp;=\u0026thinsp;179), resulting in 1053 participants for these specific analyses.\u003c/p\u003e\u003cp\u003e All study procedures were approved by the SingHealth Centralized Institutional Review Board (CIRB, Reference #2016/3089), and adhere to the principles of the Declaration of Helsinki. Written consent was obtained from all participants.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAssessment and Definitions of Vision, Hearing, Olfactory Impairments\u003c/h3\u003e\n\u003cp\u003ePresenting distance visual acuity (PDVA) was measured monocularly using a logMAR number chart (Lighthouse International, Distance VA Number Chart) at 4 m with participants wearing their habitual optical correction (if any), under standard photopic conditions (85 cd/m\u003csup\u003e2\u003c/sup\u003e). If the participants were unable to read the largest line of letters, the chart was moved to 2 m. However, if they were still unable to read any letters at 2 m, finger counting, hand movements and the ability of the eye to perceive light with a pen torch were assessed. Presence of VI was defined as PDVA worse than 20/40 (\u0026gt;\u0026thinsp;0.3 logMAR) in the better eye in accordance with the World Health Organization (WHO) criteria for visual impairment.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e We also utilized VI in the worse eye in supplementary analyses (\u003cb\u003eSupplementary Materials 2\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eHearing for each ear was quantified by a trained study coordinator using a portable pure tone audiometer (SHOEBOX Audiometer - Clearwater Clinical Limited, Ottawa, Canada) in a quiet room with background noise monitoring. Air-conduction thresholds at 500 Hz, 1000 Hz, 2000 Hz and 4000 Hz were recorded, and pure tone average (PTA) was calculated. HI was defined by PTA\u0026thinsp;\u0026gt;\u0026thinsp;25 dB in the better ear in accordance to the WHO criteria for HI.\u003csup\u003e32\u003c/sup\u003e We also conducted sensitivity analyses using HI definition in the worse ear in \u003cb\u003eSupplementary Materials 2\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eThe 16-item identification segment of the Sniffin\u0026rsquo; Sticks test battery was used to determine olfactory function. Odour impregnated felt pen tips were presented at intervals of 30 seconds of each test-odor presentation, and participants were tasked to select the correct odorant descriptor from four multiple choice questions. The number of correct answers were summed in an overall score, with the maximum score being 16.\u003csup\u003e33\u003c/sup\u003e Any OI was defined as a score of \u0026lt;\u0026thinsp;11 based on updated cut-points published by Hummel and colleagues.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eAny DSI\u003c/span\u003e was defined as any impairment of two senses as described above i.e., HI\u0026thinsp;+\u0026thinsp;VI, HI\u0026thinsp;+\u0026thinsp;OI, or VI\u0026thinsp;+\u0026thinsp;OI. NSI was defined as the absence of VI, HI and OI.\u003c/p\u003e\n\u003ch3\u003eAssessment of Health-related Outcomes\u003c/h3\u003e\n\u003cp\u003eTrained research staff conducted face-to-face interviews to collect the following questionnaire data and performed standardized clinical examinations for the clinical data. \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eHealth-Related Quality of Life (HR-QoL)\u003c/span\u003e was assessed using the EuroQoL5-Dimensions Health States (EQ-5D-5L).\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e The EQ-5D-5L assesses 5 different health states: mobility, self-care, usual activity pain/discomfort and anxiety/depression. A utility index ranging from 1 (perfect health) to -0.59 (worse health) was calculated for all participants using established UK EQ-5D tariffs.\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eLife-space mobility\u003c/span\u003e was quantified using the Life-Space Questionnaire,\u003csup\u003e38\u003c/sup\u003e which was adapted for use in a Singaporean context. The 7-item questionnaire is designed to determine the life-space accessed (e.g., house, neighborhood, country) within the past 3 days of the participant. Each item is scored 1 with \u0026lsquo;yes\u0026rsquo;, and 0 with \u0026lsquo;no\u0026rsquo;. The maximum score is 7, corresponding with the largest life space mobility possible. Low life-space mobility was defined as a score of \u0026lt;\u0026thinsp;5 (median). Presence of low \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eInstrumental Activities of Daily Living\u003c/span\u003e (IADL) was determined using the 8-item Lawton IADL scale.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Items were recoded to reflect increasing independence of the individual, with a score of 0 being the least independent and 2 being the most independent. \u0026lsquo;Dependent, low function\u0026rsquo; is defined as a total Lawton score of \u0026lt;\u0026thinsp;16. \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eFalls and fall frequency\u003c/span\u003e over the past 12 months were quantified using an in-house questionnaire; and \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ehospitalization frequency and duration\u003c/span\u003e over the past 6 months were assessed using the modified healthcare services expenditure module.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e This module was also used to assess \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003edirect healthcare expenditure\u003c/span\u003e, comprising hospitalization and emergency department visit costs over the past 6 months, and mental health and outpatient service utilization over the past 3 months, extrapolated to annual healthcare expenditure.\u003c/p\u003e\u003cp\u003eDual Energy X-Ray Absorptiometry (DXA; Discovery-W. Hologic Inc. Bedford-MA) was used to measure whole and regional body compositions, including fat and muscle mass, and bone mineral density (BMD). Based on the Asian Working Group for Sarcopenia (2019) recommended cut-offs, sarcopenia was defined as having low appendicular muscle mass (men\u0026thinsp;\u0026lt;\u0026thinsp;7 kg/m\u003csup\u003e2\u003c/sup\u003e, women\u0026thinsp;\u0026lt;\u0026thinsp;5.4 kg/m\u003csup\u003e2\u003c/sup\u003e) in the presence of either low grip strength (men\u0026thinsp;\u0026lt;\u0026thinsp;28 kg, women\u0026thinsp;\u0026lt;\u0026thinsp;18 kg) or low gait speed (\u0026lt;\u0026thinsp;1m/s).\u003csup\u003e41\u003c/sup\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eBMD\u003c/span\u003e was classified according to the WHO criteria for this age group, based on DXA measured T-scores of the lumbar spine, and/or femoral neck, and/or total hip as follows: normal (T-score \u0026gt;-1 SD), osteopenia (-1\u0026thinsp;\u0026ge;\u0026thinsp;T-score \u0026gt;-2.5 SD), and osteoporosis (T-score \u0026le; -2.5SD).\u003csup\u003e42\u003c/sup\u003e Therefore, osteoporosis was defined a low BMD (T-score, \u0026le; \u0026minus;2.5) in any of the following sites: hip, femoral, neck, and lumbar spine. \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eFrailty\u003c/span\u003e was defined according to the modified Fried criteria\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e as having 3 or more of the following conditions: shrinkage (Body Mass Index [BMI]\u0026thinsp;\u0026lt;\u0026thinsp;18.5), low gait speed (\u0026lt;\u0026thinsp;1.0m/s assessed using a 4 m gait speed test), low grip strength (men\u0026thinsp;\u0026lt;\u0026thinsp;28 kg, women\u0026thinsp;\u0026lt;\u0026thinsp;18 kg quantified using a digital hand dynamometer (JAMAR Plus+, JLW instruments, Illinois, USA)), exhaustion (score of \u0026lt;\u0026thinsp;10 for three questions from the vitality domain of the 12-item Short-form survey SF-12), low physical activity levels (defined as the sex-specific lowest quintile of total self-reported duration spent carrying out moderate and vigorous activity (e.g., gardening, brisk walking, dancing, jogging).\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eAssessment of Covariates\u003c/h3\u003e\n\u003cp\u003eParticipants\u0026rsquo; sociodemographic details, including age, sex, ethnicity, socioeconomic status (SES); self-reported medical history (presence of diabetes, hypertension, dyslipidemia, cardiovascular disease, chronic kidney disease; number of medications); and lifestyle factors (smoking status and frequency of alcohol consumption) were collected via an in-house questionnaire. \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eLow SES\u003c/span\u003e was defined as having primary or lower education and a monthly household income below \u003cspan\u003e$\u003c/span\u003e2000 SGD.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e Clinical covariates were collected via standardized clinical examination: weight and height were measured using a wall-mounted, adjustable measuring scale and a calibrated scientific weight scale, respectively. \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eBMI\u003c/span\u003e was calculated as weight in kilograms divided by height in meters squared (Weight\u003csup\u003e45\u003c/sup\u003e/Height[m]\u003csup\u003e2\u003c/sup\u003e). BMI was categorized as underweight (\u0026lt;\u0026thinsp;18.5), normal (18.5\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;23), overweight (BMI\u0026thinsp;\u0026ge;\u0026thinsp;23 to 27.5), and obese (BMI\u0026thinsp;\u0026gt;\u0026thinsp;27.5) according to Asian cut-offs.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e Systolic and diastolic blood pressure was measured twice using an automated blood pressure (Dinamap Pro Series DP110X-RW; GE Medical Systems Information Technologies, Inc), with a third reading taken if the two previous systolic or diastolic readings differed by more than 10- or 5-mm Hg, respectively. The mean of the closest two readings was used in analyses. \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eHypertension\u003c/span\u003e was defined as SBP\u0026thinsp;\u0026ge;\u0026thinsp;140mmHg, DBP\u0026thinsp;\u0026ge;\u0026thinsp;90mmHg, self-reported use of anti-hypertensive medications, or self-reported history of physician-diagnosed hypertension.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e Blood samples were collected for hemoglobin A1c (HbA1c); random glucose; total, high-density lipoprotein and low-density lipoprotein cholesterol; and triglyceride levels. \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eDiabetes\u003c/span\u003e was defined as random glucose\u0026thinsp;\u0026ge;\u0026thinsp;11.1mmol/L, HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;6.5%, self-reported use of diabetic medication or reported history of physician-diagnosed diabetes.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eDyslipidemia\u003c/span\u003e was defined as total cholesterol\u0026thinsp;\u0026ge;\u0026thinsp;5.2 mmol/L, LDL cholesterol\u0026thinsp;\u0026ge;\u0026thinsp;3.4 mmol/L, triglycerides\u0026thinsp;\u0026ge;\u0026thinsp;1.7 mmol/L or use of anti-cholesterol medication.\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003ePolypharmacy\u003c/span\u003e was considered present if the patient was taking 5 or more medications (excluding short-term medication, e.g., pain; supplements; or vitamins). \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eChronic kidney disease\u003c/span\u003e (CKD) was defined as an estimated glomerular filtration rate (eGFR)\u0026thinsp;\u0026lt;\u0026thinsp;60mL/min/1.73m\u003csup\u003e2 47\u003c/sup\u003e and \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eCVD\u003c/span\u003e was defined as having a history of angina, stroke, or heart attack. Lastly, \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003emultimorbidity\u003c/span\u003e was defined as having \u0026ge; 3 of the following systemic conditions: diabetes, hypertension, dyslipidemia, CVD, CKD.\u003c/p\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eDescriptive statistics were performed to characterize the study population. Continuous variables were described with means and SDs. Categorical variables were reported using numbers and percentages. As we oversampled minority races, females, and older participants, the overall, age-, sex-, and ethnicity-stratified prevalence rates for DSI combinations were determined by weighting individuals according to their sampling probabilities and standardizing to Singapore\u0026rsquo;s 2020 population census.\u003c/p\u003e\u003cp\u003eTo identify the determinants of the three types of DSI, we performed logistic regression analysis, including pre-defined determinants such as age, sex, ethnicity, low SES, living alone, BMI category, smoking status, alcohol consumption frequency, polypharmacy and multimorbidity into the model, followed by a dominance analysis to assess the individual contribution of each determinant to the overall model. The outcome of interest was participants with a particular type of DSI (e.g., VI\u0026thinsp;+\u0026thinsp;HI), with the reference group being those with NSI.\u003c/p\u003e\u003cp\u003eTo determine the associations between DSI and patient-centered outcomes, we performed multivariable linear regression analysis on continuous outcomes (i.e., Health-Related Quality of Life (EQ-5D-5L) and life-space mobility) and multivariable logistic regression analysis on binary outcomes (i.e., low IADL status, falls, hospitalizations, osteoporosis, frailty and sarcopenia). The reference group for the multivariable regression was NSI. We utilized two-part models to determine the associations between DSI and health care costs. The first model consists of logistic regression models and the second model consists of gamma generalized linear models with log link function. All analyseswere adjusted for potential confounders, such as age, sex, ethnicity, low SES, living alone, smoking status, polypharmacy and multimorbidity.\u003c/p\u003e\u003cp\u003eAll statistical analyses were performed using R version 4.3.1. A p-value (2-sided)\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Additional sensitivity analyses using worse eye/ear definitions for DSI were performed and provided in \u003cb\u003eSupplementary Materials 2.\u003c/b\u003e\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe any DSI group (n\u0026thinsp;=\u0026thinsp;711) was on average 75.7 \u0026plusmn;7.8 years old, of which 352 (49.5%) were female, and 348 (48.9%), 195 (27.4%), 168 (23.6%) were Chinese, Malays and Indians, respectively. A descriptive summary of the demographic, systemic, socioeconomic characteristics and health-related outcomes stratified by DSI status is provided 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\u003eDemographic, systemic, and socioeconomic characteristics of participants in the PIONEER study, stratified by DSI status (NSI, DSI)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;342)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDSI\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e \u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;711)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;1053)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eMean (SD) or n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e66.7 (5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75.7 (7.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72.7 (8.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale sex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e238 (69.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e352 (49.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e590 (56.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChinese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e163 (47.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e348 (48.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e511 (48.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMalay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e91 (26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e195 (27.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e286 (27.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e88 (25.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168 (23.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e256 (24.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow socioeconomic status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33 (9.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e129 (18.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e162 (15.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving alone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87 (12.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e105 (10.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI categories\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnderweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15 (4.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 (4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47 (4.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e89 (26.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e198 (27.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e287 (27.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverweight/Obese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e238 (69.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e479 (67.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e717 (68.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking status\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever smoked or past smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e319 (93.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e615 (86.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e934 (88.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18 (5.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70 (9.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88 (8.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol frequency\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e282 (82.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e591 (83.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e873 (82.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;4 days/week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24 (7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54 (7.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78 (7.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;4 days/week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25 (2.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolypharmacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52 (15.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e171 (24.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e223 (21.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAny systemic condition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e327 (95.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e698 (98.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1025 (97.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSystemic conditions\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e87 (25.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e272 (38.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e359 (34.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e271 (79.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e620 (87.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e891 (84.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDyslipidaemia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e290 (84.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e564 (79.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e854 (81.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCVD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42 (12.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e138 (19.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e180 (17.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCKD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26 (7.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e153 (21.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e179 (17.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultimorbidity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e104 (30.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e317 (44.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e421 (40.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e1. DSI subjects consists of 15 (2.1%) VI\u0026thinsp;+\u0026thinsp;OI subjects, 173 (24.3%) VI\u0026thinsp;+\u0026thinsp;HI subjects, and 523 (73.6%) OI\u0026thinsp;+\u0026thinsp;HI subjects.\u003c/p\u003e\u003cp\u003eBMI: Body Mass Index; CKD: Chronic Kidney Disease; CVD: Cardiovascular Disease; DSI: Dual Sensory Impairment; HI: Hearing Impairment; NSI: No Sensory Impairment; OI: Olfactory Impairment; SD: Standard Deviation; VI: Visual Impairment.\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 crude prevalence of VI\u0026thinsp;+\u0026thinsp;OI, VI\u0026thinsp;+\u0026thinsp;HI, OI\u0026thinsp;+\u0026thinsp;HI was 0.7%, 8.4% and 25.5%, respectively; and the related census-adjusted prevalence was 1.0%, 7.3% and 21.7%, respectively (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall, the weighted prevalence of DSI combinations (except VI\u0026thinsp;+\u0026thinsp;OI) increased with age (p-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Sex-stratified results revealed no difference in the prevalence between males and females in VI\u0026thinsp;+\u0026thinsp;OI group, while females had higher prevalence rates of VI\u0026thinsp;+\u0026thinsp;HI than males, both overall (9.4% in females vs 5% in males) and across age groups, and males had higher prevalence rates of OI\u0026thinsp;+\u0026thinsp;HI than females, both overall (28.8% in males vs 15.3% in females) and across age groups. Ethnicity stratified analyses showed no difference in the prevalence of DSI combinations across the three ethnic groups sampled.\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\u003eWeighted prevalence of DSI, stratified by age, sex and ethnicity in the PIONEER study.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eAge group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e\u003cp\u003eAll (N\u0026thinsp;=\u0026thinsp;2048)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c13\" namest=\"c8\"\u003e\u003cp\u003eEthnicity\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMale (N\u0026thinsp;=\u0026thinsp;919)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eFemale (N\u0026thinsp;=\u0026thinsp;1129)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eChinese (N\u0026thinsp;=\u0026thinsp;992)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003eMalay (N\u0026thinsp;=\u0026thinsp;582)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u003cp\u003eIndian (N\u0026thinsp;=\u0026thinsp;474)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWeighted, % \u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eWeighted, % \u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eWeighted, % \u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eWeighted, % \u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eWeighted, % \u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eWeighted, % \u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.0 (0.3, 2.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5 (0.3, 4.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.4 (0.0, 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.1 (0.3, 2.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.4 (0.0, 2.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e70\u0026ndash;79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.9 (0.3, 2.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.7 (0.5, 4.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.0 (0.3, 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e1.3 (0.2, 4.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.1 (0.3, 2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5 (0.2, 5.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.9 (0.1, 3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.3 (0.3, 3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP-trend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.0 (0.5, 1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.1 (0.3, 2.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.9 (0.3, 1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1.1 (0.5, 2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0.3 (0.0, 1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e0.3 (0.0, 1.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.7 (3.1, 6.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.6 (1.7, 6.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5.8 (3.3, 9.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4.5 (2.6, 7.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e6.3 (3.7, 9.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e5.1 (2.5, 9.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e70\u0026ndash;79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.3 (6.9, 12.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.9 (3.0, 10.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.2 (8.7, 16.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e9.3 (6.5, 12.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e10.3 (6.3, 15.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e7.9 (4.1, 13.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13.9 (10.0, 18.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.7 (5.5, 15.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16.5 (10.8, 23.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e14.3 (9.8, 19.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e9.6 (4.9, 16.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e13.9 (8.3, 21.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP-trend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eP-trend\u0026thinsp;=\u0026thinsp;0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003eP-trend\u0026thinsp;=\u0026thinsp;0.135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u003cp\u003eP-trend\u0026thinsp;=\u0026thinsp;0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.3 (6.0, 8.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.0 (3.4, 7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.4 (7.4, 11.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e7.3 (5.8, 9.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e7.6 (5.5, 10.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e6.9 (4.7, 9.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e60\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.9 (12.1, 18.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23.7 (18.6, 29.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.4 (3.9, 9.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e14.7 (11.3, 18.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e15.6 (11.4, 20.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e16.6 (11.6, 22.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e70\u0026ndash;79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.3 (23.4, 31.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35.1 (28.5, 42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20.6 (16.1, 25.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e26.6 (22.2, 31.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e31.4 (24.7, 38.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e31.6 (24.3, 39.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.5 (32.1, 43.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e103\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40.1 (32.4, 48.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35.9 (28.5, 44.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e37.5 (31.3, 44.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e37.5 (28.7, 47.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e38.0 (29.6, 46.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP-trend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e\u003cp\u003eP-trend\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.7 (19.5, 24.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28.8 (25.1, 32.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15.3 (13.0, 17.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e21.6 (19.0, 24.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e146\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e21.8 (18.4, 25.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003e23.1 (19.2, 27.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e\u003cp\u003eWeighted prevalences are calculated with sampling weights specific to each age group, sex and ethnicity to adjust for oversampling and post-stratification weights to align to the population distribution based on the 2020 Singapore Census. P-trend will not be computed for counts less than 5 in any age group or if the total count is less than 20. \u003c/p\u003e\u003cp\u003eCI: Confidence Interval; DSI: Dual Sensory Impairment; HI: Hearing Impairment; OI: Olfactory Impairment; VI: Visual Impairment.\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\u003eAs stated above, only 1053 participants (771 with any DSI and 342 with NSI) were included in the determinants, impact and costs analyses. Moreover, because of the low number of individuals with VI\u0026thinsp;+\u0026thinsp;OI, this DSI combination was not included in risk determinant analysis. In adjusted models (Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e) older age was significantly associated with VI\u0026thinsp;+\u0026thinsp;HI: OR 1.22 [95%CI: 1.16, 1.29] and OI\u0026thinsp;+\u0026thinsp;HI: OR 1.23 [95%CI: 1.19, 1.28]. Dominance analysis showed that age contributed 70.4% and 70.8% of the variance for VI\u0026thinsp;+\u0026thinsp;HI and OI\u0026thinsp;+\u0026thinsp;HI, respectively. Multimorbidity was associated with increased odds of VI\u0026thinsp;+\u0026thinsp;HI (OR 3.74 [95%CI 1.86, 7.69]), and contributed 10.8% of the variance, while obesity was associated with decreased odds of VI\u0026thinsp;+\u0026thinsp;HI (OR 0.19 [95%CI: 0.19, 0.77]) and contributed 2.5% of the variance.\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\u003eA. Factors associated with DSI (VI\u0026thinsp;+\u0026thinsp;HI)\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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRisk factor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eDominance analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eContribution\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRank\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.22 (1.16, 1.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\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=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\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\u003e0.89 (0.44, 1.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.742\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace\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\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChinese\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\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMalay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.20 (0.57, 2.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.628\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.89 (0.41, 1.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.752\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow socioeconomic status\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\u003cp\u003e13.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"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\u003e1.73 (0.75, 3.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.195\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving alone\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\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"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\u003e1.84 (0.62, 5.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.260\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI categories\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\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal\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\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnderweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.88 (0.18, 3.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.866\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverweight/Obese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.38 (0.19, 0.77)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.007\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking status\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\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever or past smoker\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\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.81 (0.85, 9.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.085\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol frequency\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\u003cp\u003e-1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\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\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;4 days/week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.13 (0.37, 3.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.814\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;4 days/week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.44 (0.17, 9.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.711\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolypharmacy\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\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"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\u003e0.48 (0.20, 1.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.081\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultimorbidity\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\u003cp\u003e10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"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\u003e3.74 (1.86, 7.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e1: Contribution is the standardized dominance statistics in the dominance analysis from the model.\u003c/p\u003e\u003cp\u003e2. The ranks of each predictor are ranked from predictors with the greatest contribution to the least.\u003c/p\u003e\u003cp\u003eLow Socioeconomic Status: Having primary or lower education and individual monthly income\u0026thinsp;\u0026lt;\u0026thinsp;SGD2000; BMI categories: BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e as underweight, BMI between 18.5 and 22.9 kg/m\u003csup\u003e2\u003c/sup\u003e (inclusive) as normal, BMI\u0026thinsp;\u0026ge;\u0026thinsp;23 kg/m\u003csup\u003e2\u003c/sup\u003e as overweight/obese; Polypharmacy: Taking\u0026thinsp;\u0026ge;\u0026thinsp;5 medications (exclude supplements or vitamins); Multimorbidity: Having more than or equal to 3 systemic conditions (diabetes, hypertension, dyslipidemia, CVD, CKD).\u003c/p\u003e\u003cp\u003eBMI: Body Mass Index; CI: Confidence Interval; CKD: Chronic Kidney Disease; CVD: Cardiovascular Disease; DSI: Dual Sensory Impairment; HI: Hearing Impairment; OR: Odds Ratio; VI: Visual Impairment.\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\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eB\u003c/b\u003e. Factors associated with DSI (OI\u0026thinsp;+\u0026thinsp;HI)\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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRisk factor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eModel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eDominance analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eContribution\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRank\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.23 (1.19, 1.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e70.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\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=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\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\u003e3.62 (2.26, 5.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRace\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\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChinese\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\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMalay\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.10 (0.64, 1.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.730\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.94 (0.54, 1.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.823\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow socioeconomic status\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\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"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\u003e1.09 (0.57, 2.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.791\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLiving alone\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\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"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\u003e2.37 (1.09, 5.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.033\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI categories\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\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal\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\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnderweight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.62 (0.19, 1.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.423\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOverweight/Obese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.13 (0.66, 1.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.663\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking status\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\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNever or past smoker\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\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent smoker\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.51 (1.21, 5.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.015\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlcohol frequency\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\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\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\u003cp\u003eNA\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;4 days/week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.93 (0.45, 1.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.842\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;4 days/week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.64 (0.46, 6.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.469\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolypharmacy\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\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"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\u003e0.84 (0.45, 1.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.578\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultimorbidity\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\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4\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\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\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=\"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\u003e1.11 (0.65, 1.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.701\u003c/p\u003e\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e1: Contribution is the standardized dominance statistics in the dominance analysis from the model.\u003c/p\u003e\u003cp\u003e2. The ranks of each predictor are ranked from predictors with the greatest contribution to the least.\u003c/p\u003e\u003cp\u003eLow Socioeconomic Status: Having primary or lower education and individual monthly income\u0026thinsp;\u0026lt;\u0026thinsp;SGD2000; BMI categories: BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e as underweight, BMI between 18.5 and 22.9 kg/m\u003csup\u003e2\u003c/sup\u003e (inclusive) as normal, BMI\u0026thinsp;\u0026ge;\u0026thinsp;23 kg/m\u003csup\u003e2\u003c/sup\u003e as overweight/obese; Polypharmacy: Taking\u0026thinsp;\u0026ge;\u0026thinsp;5 medications (exclude supplements or vitamins); Multimorbidity: Having more than or equal to 3 systemic conditions (diabetes, hypertension, dyslipidemia, CVD, CKD)\u003c/p\u003e\u003cp\u003eBMI: Body Mass Index; CI: Confidence Interval; CKD: Chronic Kidney Disease; CVD: Cardiovascular Disease; DSI: Dual Sensory Impairment; HI: Hearing Impairment; OI: Olfactory Impairment; OR: Odds Ratio.\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\u003eMale sex (OR 3.62 [95% CI: 2.26, 5.88]), current smoking (OR 2.51 [95% CI: 1.21, 5.40]), and living alone (OR 2.37 [95%CI 1.09, 5.40]) were associated with increased odds of OI\u0026thinsp;+\u0026thinsp;HI and contributed 13.9%, 2.9% and 2.7% of the variance, respectively.\u003c/p\u003e\u003cp\u003eIn multivariable regression models, VI\u0026thinsp;+\u0026thinsp;HI was significantly associated with lower HRQoL scores (B: -0.025 [95%CI -0.049, -0.001]). VI\u0026thinsp;+\u0026thinsp;HI and OI\u0026thinsp;+\u0026thinsp;HI were significantly associated with lower IADL status, (OR: 2.34 [95% CI 1.14, 4.81]) and (OR: 2.05 [95% CI1.12, 3.81]), respectively. We found no significant associations between DSI combinations and life space mobility, falls, hospitalizations, osteoporosis, frailty, and sarcopenia (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociations between DSI and patient-reported outcomes\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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePRO\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExposure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEstimate\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOverall marginal effect \u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eChange (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEQ-5D-5L\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.004 (-0.057, 0.066)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.004 (-0.057, 0.066)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.025 (-0.049, -0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.025 (-0.049, -0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.005 (-0.014, 0.024)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.605\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.005 (-0.014, 0.024)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLife space mobility\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.364 (-0.858, 0.130)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.364 (-0.858, 0.129)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-7.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.155 (-0.350, 0.040)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.155 (-0.350, 0.040)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-3.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.118 (-0.268, 0.032)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.118 (-0.268, 0.032)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-2.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow IADL status\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 0.92 (0.04, 6.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.01 (-0.21, 0.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-7.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 2.34 (1.14, 4.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.10 (0.01, 0.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e109.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 2.05 (1.12, 3.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.08 (0.01, 0.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e87.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFalls\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 0.60 (0.09, 2.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.07 (-0.28, 0.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-34.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 0.55 (0.27, 1.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.08 (-0.17, 0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-39.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 0.83 (0.50, 1.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.476\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.03 (-0.11, 0.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-13.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospitalisations\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 1.88 (0.09, 12.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.583\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06 (-0.18, 0.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e82.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 0.76 (0.26, 2.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.02 (-0.08, 0.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-23.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 0.79 (0.36, 1.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.556\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.02 (-0.07, 0.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-20.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOsteoporosis\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 0.48 (0.07, 2.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.11 (-0.32, 0.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-42.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 1.33 (0.75, 2.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.322\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06 (-0.06, 0.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 1.01 (0.64, 1.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.960\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00 (-0.08, 0.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFrailty\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 2.73 (0.37, 13.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.11 (-0.12, 0.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e120.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 1.60 (0.68, 3.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.275\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.04 (-0.04, 0.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e47.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 1.50 (0.75, 3.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.04 (-0.02, 0.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e40.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSarcopenia\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 1.56 (0.40, 6.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.521\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.09 (-0.19, 0.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 1.17 (0.67, 2.01)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.03 (-0.08, 0.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR: 1.23 (0.80, 1.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.04 (-0.05, 0.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e1. For PROs EQ-5D-5L, and life space mobility, the estimates are coefficients derived from linear regression models. The remaining PROs are odds ratios (OR) derived from logistic regression models.\u003c/p\u003e\u003cp\u003eAll models are adjusted for age, sex, ethnicity, low socioeconomic status, living alone, smoking status, polypharmacy and multimorbidity.\u003c/p\u003e\u003cp\u003eCI: Confidence Interval; DSI: Dual Sensory Impairment; EQ-5D-5L: EuroQoL 5-dimension 5-level; HI: Hearing Impairment; IADL: Instrumental Activities of Daily Living; NSI: No sensory impairment; OI: Olfactory Impairment; OR: Odds Ratio; PRO: Patient-Reported Outcome; VI: Visual Impairment\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\u003eAssociations between DSI and those with incurred health care costs were significant for the OI\u0026thinsp;+\u0026thinsp;HI group, which showed a trend towards substantially higher cost ratios of 2.09 [95% CI: 0.82, 5.36] compared to NSI (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssociations between DSI and costs using two-parts model.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eExposure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eFirst part\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eSecond part\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eOverall marginal effect*\u003c/p\u003e\u003cp\u003e(95% CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCost Ratio (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealthcare cost (in SGD)\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=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRobust\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReference\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNA\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\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;OI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.67 (0.14, 2.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.581\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.39 (0.05, 45.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-197.81 (-488.59, 92.98)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.72 (0.41, 1.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.234\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.49 (0.82, 8.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e293.76 (-311.81, 899.34)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOI\u0026thinsp;+\u0026thinsp;HI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.74 (0.49, 1.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.09 (0.82, 5.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.063\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e210.91 (-115.96, 537.77)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eIn the two-parts model, the first part results were odds ratios from logistic regression models and the second part results were cost ratios (exponentiated coefficients) from gamma generalised linear models with a log-link function for healthcare cost.\u003c/p\u003e\u003cp\u003eAll models are adjusted for age, sex, ethnicity, low socioeconomic status, living alone, smoking status, polypharmacy and multimorbidity.\u003c/p\u003e\u003cp\u003e* The costs were shown in SGD. Based on the exchange rate of 1 SGD to 0.74515 USD on 31 Dec 2022, the USD equivalent costs were \u0026minus;\u0026thinsp;147.40, 218.90 and 157.16 for VI\u0026thinsp;+\u0026thinsp;OI, VI\u0026thinsp;+\u0026thinsp;HI and OI\u0026thinsp;+\u0026thinsp;HI, respectively.\u003c/p\u003e\u003cp\u003eCI: Confidence Interval; DSI: Dual Sensory Impairment; HI: Hearing Impairment; NSI: No Sensory Impairment; OI: Olfactory Impairment; OR: Odds Ratio; PRO: Patient-Reported Outcome; VI: Visual Impairment\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\u003eUsing worst eye/worst ear definitions (\u003cb\u003eSupplementary Materials 2)\u003c/b\u003e, census-adjusted prevalence rates were slightly higher as expected: census-adjusted prevalence of VI\u0026thinsp;+\u0026thinsp;OI, VI\u0026thinsp;+\u0026thinsp;HI, and OI\u0026thinsp;+\u0026thinsp;HI was 2.0%, 22.0% and 15.0%, respectively. Further analyses of risk factors showed older age and smoking were associated with VI\u0026thinsp;+\u0026thinsp;HI, while age, male sex and smoking were associated with OI\u0026thinsp;+\u0026thinsp;HI. Surprisingly, except for VI\u0026thinsp;+\u0026thinsp;OI that was associated with lower odds of osteoporosis (OR 0.112 [CI: 0.006, 0.600]), no significant associations between DSI categories and any other patient centred outcomes was observed.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn our nationally representative sample of older Singaporean adults, we found for the first time that of the three DSI combinations, OI\u0026thinsp;+\u0026thinsp;HI was most prevalent, in over one in five participants. Several sociodemographic (older age, male sex, living alone), lifestyle (smoking), and health-related factors (multimorbidity) were associated with the DSI combinations assessed, with older age being the major driving factor overall. Several DSI combinations were associated with lower HR-QoL scores and a low IADL status. Only those with OI\u0026thinsp;+\u0026thinsp;HI incurred a substantially higher healthcare cost than those without. Our findings demonstrate the importance of screening for DSI combinations, particularly OI\u0026thinsp;+\u0026thinsp;HI, in older male adults and those who smoke and live alone for early detection and timely management via relevant intervention strategies such as hearing aids, ophthalmic aids or possible olfactory training. Longitudinal studies are needed to determine the predictors of incident DSI combinations and gain a deeper understanding of underlying mechanisms.\u003c/p\u003e\u003cp\u003eAs our study is the first population-based study to report on the prevalence of \u0026ldquo;OI+\u0026rdquo; DSI combinations, it is difficult to compare results pertaining to such combinations to existing literature. However, the VI\u0026thinsp;+\u0026thinsp;HI prevalence rate of 7.3% is comparable to previously reported VI\u0026thinsp;+\u0026thinsp;HI prevalence rates in Singaporean studies. For example, Phua and colleagues reported a self-reported DSI prevalence rate of 12.8%\u003csup\u003e48\u003c/sup\u003e in a large population-based study of 4077 participants, while Tareque and associates found a prevalence rate of 11.6%\u003csup\u003e49\u003c/sup\u003e in their large population-based study of 3452 subjects (self-reported VI and HI). Elsewhere in Asia, a small Malaysian study of 229 community-dwelling subjects reported a prevalence rate of 8.3%\u003csup\u003e50\u003c/sup\u003e for VI\u0026thinsp;+\u0026thinsp;HI (objectively assessed HI and VI), while two larger population-based studies of older adults in Malaysia (objectively assessed HI and VI)\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e and Japan\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e (self-reported VI and HI) reported prevalence rates of 10.5% and 11.4%, respectively. These slight inconsistencies may be explained by different methods of sensory assessment (e.g., self-report vs objective measurement) and varying definitions of VI and HI (self-reported vs objectively assessed), different characteristics of participants (e.g., older age, more comorbidities), and different access to health care facilities across countries (e.g., rural vs. urban areas). Our finding that OI\u0026thinsp;+\u0026thinsp;HI was the most prevalent combination of DSI compared to VI\u0026thinsp;+\u0026thinsp;HI or VI\u0026thinsp;+\u0026thinsp;OI in Asian older adults, could be attributed to OI and HI being closely related senses. Studies have demonstrated that conductive smell and hearing disorders are often comorbid, such as chronic rhinosinusitis and otitis media.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e Furthermore, both these senses are often the most vulnerable to a wide range of chemcial and auditory environmental pollutants/damage, and have limited capacity for regeneration, particularly among older adults.\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e The fact that OI\u0026thinsp;+\u0026thinsp;HI is the most prevalent DSI combination in our study participants highlights the need for community-based initiatives to screen for OI-related DSI in at-risk older adult populations.\u003c/p\u003e\u003cp\u003eIt is noteworthy that \u0026lt;\u0026thinsp;1% of our population were using hearing aids. While vision may be considered more vital to patients, and thus patients are more likely to either undergo corrective surgery or wear glasses to help them correct their VI, this may be less so for HI, and even less so for OI. There may also be less surgically correctable diseases for HI and OI compared with VI, meaning that prevention may be more important than cure.\u003c/p\u003e\u003cp\u003eSimilar to previous studies\u003csup\u003e\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e that have reported older age as a risk factor of DSI, the present study confirmed age as a major determinant of three combination DSI. The presence of DSI in older individuals is likely due to age-related anatomical and physiological changes of the sensory systems.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e VI among older adults can, for example, can be explained by pupillary miosis; and increased rates of cataract\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e and age-related macular degeneration;\u003csup\u003e58\u003c/sup\u003e HI may be due to degeneration of the neural elements, metabolic changes, and stiffening of membranes in the inner ear,\u003csup\u003e59\u003c/sup\u003e and OI caused by head trauma, exposure to environmental pollutants and chemicals, and age related reductions in the number of olfactory receptor cells, cell regeneration and structural and functional changes in the olfactory system.\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e Other studies have also reported the association of DSI and male sex.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e We found that male sex was significantly associated with over a 3 to 4-fold increased odds of OI\u0026thinsp;+\u0026thinsp;HI, similar to a finding where male sex was reported as a risk factor for HI\u003csup\u003e63\u003c/sup\u003e and OI.\u003csup\u003e64\u003c/sup\u003e This may be because men are more likely to work in environments with harmful noise exposure often associated with hearing loss.\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e Moreover, men may have higher exposure to industrial chemicals (including cadmium, chromium, nickel, acrylate, styrene, toluene, formaldehyde, etc.) which are known to be both olfactotoxic and ototoxic.\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e Living alone has also been identified by previous studies as a risk factor for DSI,\u003csup\u003e68\u003c/sup\u003e corroborating our findings of an increased likelihood of OI\u0026thinsp;+\u0026thinsp;HI in those living alone. Importantly, being a current smoker was significantly associated with almost a threefold increased odds of OI\u0026thinsp;+\u0026thinsp;HI, with similar results being shown in previous studies.\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e These findings highlight the need for targeted messaging about the negative impact of smoking on sensory health.\u003c/p\u003e\u003cp\u003eNext, multimorbidity showed an almost 4-fold increased odds for VI\u0026thinsp;+\u0026thinsp;HI, suggesting the need for further investigation on potential underpinning mechanisms. Various neuropathic and angiopathic manifestations consequent to diabetes, dyslipidemia, hypertension, CKD, and CVD might be a related plausible explanation.\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e,\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e For example, individuals with diabetes or CVD may develop microangiopathic changes in the retina and cochlea which may decrease microcirculation to these areas, potentially resulting in sensory impairment. Surprisingly, obesity showed a decreased odds on VI\u0026thinsp;+\u0026thinsp;HI; this might be a case of obesity paradox, again suggesting the need for more research.\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e However, its worth considering if these are simply associations, in which case DSI is a marker of a more general decline but not causally implicated in changes that otherwise lead to the conditions listed - \u003cb\u003eOR\u003c/b\u003e - are there plausible causal pathways, such as OI could be related to a shift in food preferences or appetite that can lead to dietary changes that could support the development of chronic nutrition diseases such as diabetes.\u003c/p\u003e\u003cp\u003eLike other studies,\u003csup\u003e68,73\u003c/sup\u003e we found an association between VI\u0026thinsp;+\u0026thinsp;HI and a decreased HR-QoL scores. However, other DSI combinations did not show these associations, and this might be because the EQ-5D-5L is a generic HR-QoL questionnaire and may be insensitive at measuring the impact of specific sensory impairments. Hence, other sensory-impairment specific QoL instruments might be more useful in DSI future research.\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e,\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e Moreover, we found that VI\u0026thinsp;+\u0026thinsp;HI and OI\u0026thinsp;+\u0026thinsp;HI was associated with increased odds of low IADL status, like the population-based study of 4214 older adults in Japan by Tomida and associates.\u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e This finding is not unexpected given that performing daily activities can be more difficult in the presence of sensory losses.\u003c/p\u003e\u003cp\u003eUnlike other studies,\u003csup\u003e77\u0026ndash;79\u003c/sup\u003e we found no significant relationship between all DSI combinations and falls and hospitalization. This may be due to the concept of \u0026lsquo;silent-fallers\u0026rsquo;, as many elderly do not report their falls or may not be able to recall them, resulting in a recall bias in our study.\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e This is complicated by the fact that we were unable to access participant\u0026rsquo;s medical history and history of falls to verifying participant self-report due to Singapore\u0026rsquo;s strict data protection laws. Additionally, any DSI combination was not associated with frailty and sarcopenia in our study, a finding which aligns with some studies and not others.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e Future research is warranted in this area.\u003c/p\u003e\u003cp\u003eHealth care cost ratios was significantly higher for OI\u0026thinsp;+\u0026thinsp;HI group, and is in line with the study of Ding and colleagues, which shows that DSI (VI\u0026thinsp;+\u0026thinsp;HI) is associated with higher inpatients and outpatient costs\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and the study of Deardorff and colleagues (VI\u0026thinsp;+\u0026thinsp;HI).\u003csup\u003e28\u003c/sup\u003e To our knowledge, this is the first DSI study performed in Asia analyzing the economic impact of DSI combinations using objectively assessed sensory impairments, and it clearly shows the stark economic disparity DSI patients are coping with. These numbers imply that policymakers should consider creating specialized subsidy programs to alleviate this economic burden for this growing group of older adults.\u003c/p\u003e\u003cp\u003eStrengths of this study include a well-characterized, representative sample of older Singaporeans, the objective assessment of sensory impairments and the inclusion of OI which is rarely included in most DSI studies despite its high burden. We supply additional analysis using the worse eye and ear which allowed us to capture those with unilateral as well as bilateral disease, creating a more accurate picture of the continuum of sensory impairments and thus making our study more inclusive. It also creates the future opportunity to investigate whether those with unilateral DSI vs bilateral DSI might benefit from earlier interventions to either prevent or mitigate their sensory impairments as early as possible.\u003c/p\u003e\u003cp\u003eHowever, several limitations should also be noted. Audiometry was performed using pure tones between 500 and 4000hz, to calculate a pure tone average. Higher frequencies were not tested, thus participants with only high frequency hearing loss were not accounted for in this study. Also, other sensory impairments such as taste and tactile dysfunction were not investigated, which may also have impacted on our health-related outcome analyses. Next, due to the low numbers of the VI\u0026thinsp;+\u0026thinsp;OI group (n\u0026thinsp;=\u0026thinsp;15), potential risk factors could unfortunately not be presented, and future research with more VI\u0026thinsp;+\u0026thinsp;OI subjects is warranted. Lastly, any causal effects are unknown due to the cross-sectional design of our study. Longitudinal studies are needed to clarify directionality of the associated factors discovered in this study. To elucidate this, a 4.5-year follow-up visit for the PIONEER study (PIONEER II) has started, which will help to understand the changing prevalence of DSI better, determine the directionality of potential risk factors and gain a better understanding of the impact of DSI.\u003c/p\u003e\u003cp\u003eIn conclusion, our study found for the first time that OI\u0026thinsp;+\u0026thinsp;HI was the most common type of DSI in Asian older adults, which was associated with a series of chronic diseases and also incurred a substantially higher healthcare cost than those without. Older age exerted the largest influence across all types of DSI. Several DSI types were associated with lower HR-QoL scores and a low IADL status. Screening for DSI, particularly OI\u0026thinsp;+\u0026thinsp;HI is warranted for early detection and timely management in this growing group of elderly. Future longitudinal research is needed to further explore the relationships between DSI combinations, its risk factors, and associated dietary and behavioral adaptations and patient-centered and economic burdens.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding/Support:\u0026nbsp;\u003c/strong\u003eProfessor Lamoureux is supported by the\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNational Medical Research Council Senior Clinician Scientist Award (CSA-NMRC-CSA-SI #JRNMRR197001 and NMRC-CSA-SI #JRNMRR140601).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of Funders/Sponsors:\u003c/strong\u003e The funding sources had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or in the decision to submit the manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e: Drs Gupta and Lamoureux had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudy concept and design\u003c/em\u003e: Gupta, Nooteboom and Lamoureux\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcquisition, analysis, or interpretation of data\u003c/em\u003e: Gupta, Nooteboom, Wong, Fenwick, Man, and Lamoureux.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDrafting of manuscript\u003c/em\u003e: Gupta, Nooteboom, Fenwick, Man, and Lamoureux.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCritical revision of the manuscript for important intellectual content\u003c/em\u003e: Gupta, Nooteboom, Fenwick, Man, Wong, Forde, Yeo, Gao, Tan, Yee, Ng, Teo and Lamoureux.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eObtained funding:\u003c/em\u003e Lamoureux\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistical analysis\u003c/em\u003e: Wong\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAdministrative, technical, or material support:\u003c/em\u003e Gupta\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudy Supervision:\u003c/em\u003e Gupta, Lamoureux\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eADDITIONAL INFORMATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u003c/strong\u003e All authors have no conflict of interest and there are no competing financial and non-financial interests.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. All requests will be considered in accordance with institutional and ethical guidelines.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNations, U. \u003cem\u003eWorld Population Ageing 2019: Highlights\u003c/em\u003e (United Nations, 2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eST/ESA/SER.A/430\u003c/span\u003e\u003cspan address=\"http://ST/ESA/SER.A/430\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKaneda, H. et al. Decline in taste and odor discrimination abilities with age, and relationship between gustation and olfaction. \u003cem\u003eChem. Senses\u003c/em\u003e. \u003cb\u003e25\u003c/b\u003e (3), 331\u0026ndash;337 (2000).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGates, G. A., Mills, J. 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L. \u0026amp; How, C. H. Approach to falls among the elderly in the community. \u003cem\u003eSingap. Med. J.\u003c/em\u003e \u003cb\u003e61\u003c/b\u003e (3), 116\u0026ndash;121 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao, Y. et al. Combined Vision and Hearing Impairment is Associated with Frailty in Older Adults: Results from the West China Health and Aging Trend Study. \u003cem\u003eClin. Interv Aging\u003c/em\u003e. \u003cb\u003e17\u003c/b\u003e, 675\u0026ndash;683 (2022).\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":"DSI, Epidemiology, Risk factors, Determinants, Patient Centered Impact, Health Care costs, Productivity costs","lastPublishedDoi":"10.21203/rs.3.rs-7920823/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7920823/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe aimed to determine the prevalence, risk factors, patient-centered impact and health-related costs of three types of dual sensory impairment (DSI) in a multi-ethnic older Asian population.\u003c/p\u003e\u003cp\u003eIn this population-based, cross-sectional study (2017\u0026ndash;2022) of 2,048 Asian adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years, vision, hearing and olfactory impairments (VI, HI and OI) were assessed using validated clinical tests. DSI types included: VI\u0026thinsp;+\u0026thinsp;HI, VI\u0026thinsp;+\u0026thinsp;OI, and HI\u0026thinsp;+\u0026thinsp;OI. Age-, sex-, and ethnicity-adjusted prevalence rates (2020 Singapore Census) were calculated. Regression analyses identified associated risk factors, impacts and healthcare costs.\u003c/p\u003e\u003cp\u003eOf the 2,048 participants (mean age\u0026plusmn;standard deviation [SD] 75.7\u0026plusmn;7; 49.5% female), prevalence rates of VI\u0026thinsp;+\u0026thinsp;OI, VI\u0026thinsp;+\u0026thinsp;HI, OI\u0026thinsp;+\u0026thinsp;HI were 1.0%, 7.3% and 21.7%, respectively. Older age (OR1.22) and multimorbidity (OR3.74) were significantly associated with VI\u0026thinsp;+\u0026thinsp;HI, while older age (OR1.23), males (OR3.62), living alone (OR2.37) and current smoking (OR2.51) were associated with higher odds of OI\u0026thinsp;+\u0026thinsp;HI. VI\u0026thinsp;+\u0026thinsp;HI was associated with lower HRQoL-scores (β: -0.025), while VI\u0026thinsp;+\u0026thinsp;HI (OR2.34) and OI\u0026thinsp;+\u0026thinsp;HI (OR2.05) were associated with lower IADL status. Significantly higher healthcare costs (2-fold) were found for OI\u0026thinsp;+\u0026thinsp;HI compared to those without.\u003c/p\u003e\u003cp\u003eDSI, particularly OI\u0026thinsp;+\u0026thinsp;HI, is relatively prevalent in older Singaporean adults. Early identification and targeted screening of at-risk groups may mitigate adverse outcomes and healthcare cost, given the global ageing population.\u003c/p\u003e","manuscriptTitle":"Elucidating The Burden of Dual-Sensory Impairment in Community-based Older Individuals in a Multi- Ethnic Society","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-13 08:12:23","doi":"10.21203/rs.3.rs-7920823/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-13T10:30:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-23T10:41:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"47674731683349620876275240133919704355","date":"2025-12-10T12:25:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-16T12:08:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"84080365455766750598190401893844682288","date":"2025-11-13T10:57:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"89029001291924396415366530571723696596","date":"2025-11-12T03:25:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-03T04:06:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-03T04:03:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-31T13:34:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-29T10:04:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-29T09:34:56+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":"d775884c-f8dc-4fa9-9e21-9e826a8f1d39","owner":[],"postedDate":"November 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":57767892,"name":"Health sciences/Diseases"},{"id":57767893,"name":"Health sciences/Health care"},{"id":57767894,"name":"Health sciences/Medical research"},{"id":57767895,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-04-07T16:04:43+00:00","versionOfRecord":{"articleIdentity":"rs-7920823","link":"https://doi.org/10.1038/s41598-026-40484-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-04-02 15:59:53","publishedOnDateReadable":"April 2nd, 2026"},"versionCreatedAt":"2025-11-13 08:12:23","video":"","vorDoi":"10.1038/s41598-026-40484-9","vorDoiUrl":"https://doi.org/10.1038/s41598-026-40484-9","workflowStages":[]},"version":"v1","identity":"rs-7920823","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7920823","identity":"rs-7920823","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}