Examining associations of changes in social connectedness with healthcare utilization and costs: A prospective study among Singapore adults

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This longitudinal study examined how temporal changes in social connectedness impact subsequent healthcare utilization and costs. Data from a population health survey were linked with an administrative healthcare database, and participants without any records were excluded. Social isolation and loneliness were assessed with the Lubben Social Network Scale-6 and three-item UCLA Loneliness Scale, respectively. Baseline characteristics were compared using Chi-square or Kruskal-Wallis H tests. Two-step hurdle models investigated the associations between status change and subsequent healthcare utilization and costs, adjusting for baseline values and covariates. Among 1,182 participants (55% female; 61.3% aged < 60), 11.2% became socially disconnected and 15.2% became socially connected. Persistent social disconnection (16.9%) was associated with increased hospitalizations, polyclinic visits, and ED visits, and higher hospitalizations and ED costs, at both one-year and three-year follow-ups, compared to those who remained socially connected (56.7%). Becoming socially connected showed protective effects for subsequent hospitalizations and polyclinic visits, but not for ED visits and associated costs. Among healthcare users, alleviating social isolation and loneliness could help reduce costly hospitalizations and ease resource strains on polyclinic services. Health sciences/Health care Health sciences/Medical research Social isolation loneliness healthcare utilization healthcare cost longitudinal study Figures Figure 1 Introduction Social isolation reflects objective measures of social connectedness, such as the number and frequency of contacts an individual has with family and friends, whilst loneliness captures the subjective distress caused by perceived discrepancies between existing and desired social relationships 1 . These distinct social phenomena are growing concerns in large, industrialized societies which have become increasingly fragmented due to a multitude of factors, including urbanization and shifts towards an aging population as well as nuclear family structures 2 – 5 . In 2025, the World Health Organization Commission on Social Connection issued a landmark report recognizing social isolation and loneliness as pressing public health challenges in many countries and urging policymakers and stakeholders to prioritize interventions addressing these issues 6 . A national online survey in the United States reported that the proportion of adults experiencing loneliness has been trending upwards, from 46% in 2018 to 58% in 2023 7 , and a survey among European Union countries found that over 35% of respondents had experienced loneliness at least sometimes in 2022 8 . There were similar observations in developed Asian countries, with loneliness estimated to be affecting approximately one-third of the general population in Korea and Japan 9 , 10 . On social isolation, research has focused primarily on older adults, with a meta-analysis of 41 studies by Teo et al. (2023) revealing a pooled global prevalence of 25% in this demographic 11 . Social isolation and loneliness are critical social determinants of health, associated with profound detrimental effects on both physical and mental health outcomes, including elevated risk of premature mortality 12 , increased severity of depression 13 , 14 , and greater susceptibility to unhealthy behaviors 15 , which could contribute to increased healthcare needs and utilization. Investigations into the relationships between social isolation, loneliness, and healthcare utilization have yielded mixed findings, with results varying by study design and outcome measurement approach. Studies utilizing administrative data have consistently found associations with increased hospitalizations 16 , emergency department (ED) visits 16 , 17 , and general practitioner (GP) visits 17 . However, studies relying on self-reported healthcare utilization have produced more variable results, with some noting increased hospitalizations 18 , ED visits 18 , 19 , and GP visits 18 , 20 , 21 , while others found no significant associations with hospitalizations 21 , 22 and primary care use 23 . These mixed findings suggest there may be multiple competing mechanisms, with some being more influential depending on factors such as the population studied, healthcare system characteristics, and research study approaches. Beyond healthcare demand and resource allocation challenges, social isolation and loneliness also impose substantial economic burdens. For instance, Mira et al. (2024) observed that lonely older adults incurred €802.18 more in healthcare costs annually compared to those who were socially connected 24 . In Singapore, several key demographic trends – an ageing population, rising proportion of singles, and more individuals living alone – could have contributed to the growing prevalence of social isolation and loneliness 15 , 25 . As individuals age, they may be more susceptible to social isolation and loneliness as their social network size reduces or when they encounter adverse life events such as unemployment or the development of disabilities 26 , 27 . Moreover, as a metropolitan city undergoing digital transformation, Singapore faces another layer of complexity in social connection patterns. The rapid digitalization and integration of technologies and social media in daily life present a double-edged sword: although digital platforms and solutions may offer promising opportunities to enhance social connectivity, particularly for vulnerable populations such as older adults with limited mobility, maladaptive use could paradoxically exacerbate social isolation and loneliness by reducing in-person, meaningful interactions and authentic relationships 28 – 30 . Given these key population trends and the dynamic nature of social isolation and loneliness, it is important to better understand the effects of changes in social disconnection on healthcare utilization as this can reveal critical windows for healthcare planning and intervention design. Lim & Chan (2017) observed that persistently lonely older adults were less likely to use primary care services in the past month based on self-reported data 31 , but no local study has examined how changes in both social isolation and loneliness status affect subsequent healthcare utilization and in the longer term. Importantly, social isolation and loneliness share common risk factors, such as living alone and being widowed or divorced 32 , and evidence suggests that both should be addressed concurrently to achieve marked improvements in overall health and wellbeing 32 , 33 . This present study examines social isolation and loneliness together under the broader concept of social connectedness to assess its impact on healthcare utilization and cost outcomes. The primary study objective is to investigate the associations of temporal changes in social connectedness with subsequent healthcare utilization and cost among the adult population in Singapore in four care settings: in-patient wards, EDs, specialist outpatient clinics (SOCs), and polyclinics. Specifically, this study seeks to address two research questions: What are the associations of changes in social connectedness with healthcare utilization patterns in different care settings at one-year and three-year follow-ups? What are the associations of changes in social connectedness with gross healthcare cost in different care settings at one-year and three-year follow-ups? Compared to those who remained socially connected, our hypotheses are: Individuals with persistent social disconnection will exhibit significantly higher healthcare utilization and associated costs in the respective care settings at both follow-ups. Individuals with transient social disconnection will demonstrate higher healthcare utilization and associated cost in the respective care settings at both follow-ups, albeit to a lesser extent than those with persistent social disconnection. Methods Study design and participants Data were derived from the first two waves of the Population Health Index (PHI) Study Phase 1, conducted annually in 2015 and 2016, which comprised a random sample of Singapore citizens and permanent residents aged 21 years and above residing in the Central region. The development of the PHI survey instruments, stratified sampling methodology, and data collection procedures have been detailed elsewhere 13 , 34 . The PHI study received ethical approval from the National Healthcare Group Domain Specific Review Board (Reference Number: 2015/00269). All methods were performed in accordance with the relevant guidelines and regulations. A total of 1,942 adults completed the first survey (response rate of 53.3%), of whom 1,704 (87.7%) provided additional consent to link their survey responses with administrative databases for research purposes. For individuals who consented, their PHI survey responses were linked with healthcare utilization data extracted from the institution’s central data repository. Participants were excluded if they: 1) had missing social isolation or loneliness scores in either survey, or 2) were not NHG Health patients. This resulted in a final sample of 1,182 for analysis. The participant selection process is illustrated in Fig. 1 . Measures Social isolation Social isolation was assessed using the Lubben Social Network Scale-6 (LSNS-6), a validated instrument that measures social connectedness 35 . The scale comprises two subscales (family and friend), with three questions each, scored on a 6-point Likert scale ranging from 0 (none) to 5 (nine or more): 0 = 0, 1 = 1, 2 = 2, 3 = 3–4, 4 = 5–8, 5 = ≥ 9. The six questions were: 1) “How many [relatives/friends] do you see/hear from at least once a month?”, 2) “How many [relatives/friends] do you feel at ease with whom you can talk about private matters?”, and 3) “How many [relatives/friends] do you feel close to such that you could call on them for help?”. The scale demonstrated good internal consistency in this study (Cronbach's alpha = 0.80 for the overall scale; 0.80 and 0.81 for the family and friend subscales respectively). The total score (range: 0–36) was calculated by summing up all six item scores. Following established thresholds, participants were categorized as socially isolated if the total score ranged between 0–12 35 . Loneliness Loneliness was assessed using the University of California Los Angeles (UCLA) Loneliness Scale consisting of three questions: 1) “How often do you feel that you lack companionship?”, 2) “How often do you feel left out?”, and 3) “How often do you feel isolated from others?” 36 . Each question has three frequency-related response options: 1 = Hardly ever, 2 = Some of the time, 3 = Often. The scale demonstrated good overall internal reliability in this study (Cronbach’s alpha = 0.87). The total score (range: 0–9) was calculated by summing up all three item scores. Based on the summed scores, participants were categorized as either lonely (total score: 6–9) or not lonely (total score: 3–5) 37 . Change in social connectedness First, a binary variable for social connectedness was created to classify participants as either socially connected (not isolated and not lonely, coded as 0) or socially disconnected (socially isolated and/or lonely, coded as 1) for each time point. Thereafter, this study’s independent variable, a four-level categorical variable, was constructed to capture temporal changes in social connectedness between the first and follow-up surveys: remained socially connected (socially connected in both surveys, coded as 0), became socially connected (socially disconnected in the first survey but socially connected at follow-up survey, coded as 1), remained socially disconnected (socially disconnected in both surveys, coded as 2), and became socially disconnected (socially connected in the first survey but socially disconnected at follow-up survey, coded as 3). Healthcare utilization and cost Healthcare utilization and gross cost across four care settings (inpatient wards, EDs, SOCs, and polyclinics) were extracted for three time points: one year prior to the first survey (establishing the baseline healthcare utilization and cost), one year after the follow-up survey, and three years after the follow-up survey (cumulative). Covariates We also extracted baseline socio-demographic factors including age group (younger adults < 60 years, older adults ≥ 60 years), sex (male, female), ethnicity (Chinese, non-Chinese), education (post-secondary school & above, secondary school & below), employment status (employed, not employed), marital status (married, single / divorced / widowed/ separated), living alone (yes, no), and perceived money insufficiency for basic living needs (yes, no); health-related data included number of chronic conditions (0–1, ≥ 2) out of a list of 17 conditions 38 and depressive symptoms measured using the Patient Health Questionnaire-9 (PHQ-9) 39 . Multicollinearity among covariates was assessed using Variance Inflation Factors (VIF). With all adjusted generalized VIF values below 2, there are no significant multicollinearity concerns 40 , 41 . Sample size calculation To determine the minimum required sample size, the following formula for regression analyses, with an assumption of a medium effect size (significance level of 5% and statistical power of 80%) between the independent variables (IVs) and dependent variable (DV), was utilized: N ≥ 50 + 8 m , where m is the number of IVs in the model 42 . For this approach, each level of a categorical variable would be counted as one IV 42 . For instance, the continuous PHQ-9 variable is one IV while the categorical change in social connectedness variable with four levels would be counted as four IVs. With 23 IVs in total, the minimum sample size required was 234 (50 + (8 x 23) = 234). This study’s sample of 1,182 participants is therefore adequate. Statistical analysis Demographics and covariates from the first survey formed the baseline and were summarized for the overall study population and by changes in social connectedness. Categorical variables were presented as frequencies and percentages, while continuous variables were described using means and standard deviations (SD). For categorical variables, between-group differences were assessed using Chi-squared tests. As the continuous variables in this study follow non-normal distributions, both mean [SD] and median [interquartile range (IQR)] were reported, and non-parametric Kruskal-Wallis H tests were used for comparison across groups. Healthcare utilization and costs were analyzed separately for each care setting as the dependent variable at two timepoints: one year and three years (cumulative) following the completion of the follow-up survey. Given the excess zeros and right-skewed distribution characteristic of healthcare utilization data, a two-step hurdle model was selected for the analyses of both healthcare utilization and costs 43 , 44 . For healthcare utilization, healthcare visits were first dichotomized (0: no visits; 1: ≥1 visit), and logistic regressions were conducted, controlling for baseline utilization and covariates. The coefficients were exponentiated, and results were presented as odds ratios (OR) with 95% confidence intervals (CIs). In the second step, participants with zero utilization were excluded, and a generalized linear model (GLM) with Poisson distribution was fitted. Testing for overdispersion was then performed to detect potential violation of the Poisson model assumption of equal mean-variance relationship that could lead to inflated Type 1 error rates in hypothesis testing 45 . Overdispersion was assessed using the performance package and check overdispersion function in R Studio 46 . Values more than 1 would indicate that the variance is larger than the mean, and a p-value of < 0.05 would suggest that the overdispersion is significant and the Poisson model assumption is violated. For hospitalizations and ED visits in the subsequent one year, no overdispersion was detected and analysis was conducted using Poisson GLMs. For the other care settings and in the cumulative third year, overdispersion was detected and negative binomial GLMs were employed instead. The coefficients were exponentiated, and results were expressed as incidence rate ratios (IRR) with 95% CIs. Similarly, for the first step, healthcare costs were dichotomized (0: no cost incurred; 1: cost incurred) and logistic regressions were conducted, controlling for baseline cost and covariates. Coefficients were exponentiated and results were presented as ORs with 95% CIs. In the second step, GLM regression with Gamma distribution and log link was employed to account for the typically right-skewed distribution of cost data among users, controlling for baseline covariates. Coefficients were exponentiated, and results were expressed as cost ratios (CR) with 95% CIs. All analyses were conducted using R Studio version 4.5.0, with statistical significance set at p < 0.05. Results Baseline characteristics The majority of the 1,182 participants were younger adults (61.3%), female (55.0%), of Chinese ethnicity (78.8%), attained post-secondary school education (40.9%), employed (60.7%), married (72.3%), not living alone (89.2%), had perceived money sufficiency (84.3%), and no chronic conditions (67.2%). Between the first and follow-up surveys, approximately 3 in 10 participants experienced changes in social connectedness. A slightly higher proportion became socially connected (15.2%) compared to those who became socially disconnected (11.2%). More than half of the participants (56.7%) remained socially connected, while 16.9% were persistently socially disconnected. The persistently socially disconnected group was predominantly older adults (62.0%), had secondary school education or below (87.0%), were not employed (61.5%), reported perceived money insufficiency (39.5%), and had multiple chronic conditions (54.5%). Mean PHQ-9 score was the highest in the persistently isolated and/or lonely group (Mean = 2.4, SD = 3.7) and the lowest among those who remained socially connected (Mean = 0.7, SD = 1.4). Detailed participant characteristics at baseline are presented in Table 1 . Table 1 Baseline characteristics of study participants by changes in social connection (n = 1,182). Characteristics Overall n (%) (n=1,182) Remained socially connected n (%) (n=670, 56.7%) Became socially connected n (%) (n=180, 15.2%) Remained socially disconnected n (%) (n=200, 16.9%) Became socially disconnected n (%) (n=132, 11.2%) P-value Age <0.001 a Younger adults (< 60 years old) 725 (61.3%) 468 (69.9%) 99 (55.0%) 76 (38.0%) 82 (62.1%) Older adults (≥ 60 years old) 457 (38.7%) 202 (30.1%) 81 (45.0%) 124 (62.0%) 50 (37.9%) Gender <0.001 a Female 650 (55.0%) 367 (54.8%) 108 (60.0%) 112 (56.0%) 63 (47.7%) Male 532 (45.0%) 303 (45.2%) 72 (40.0%) 88 (44.0%) 69 (52.3%) Ethnicity 0.126 a Chinese 932 (78.8%) 530 (79.1%) 137 (76.1%) 158 (79.0%) 107 (81.1%) Non-Chinese 250 (21.2%) 140 (20.9%) 43 (23.9%) 42 (21.0%) 25 (18.9%) Highest education attained <0.001 a Post-secondary school & above 484 (40.9%) 366 (54.6%) 53 (29.4%) 26 (13.0%) 39 (29.5%) Secondary school & below 698 (59.1%) 304 (45.4%) 127 (70.6%) 174 (87.0%) 93 (70.5%) Employment status <0.001 a Employed 717 (60.7%) 455 (67.9%) 107 (59.4%) 77 (38.5%) 78 (59.1%) Not employed 465 (39.3%) 215 (32.1%) 73 (40.6%) 123 (61.5%) 54 (40.9%) Marital status <0.001 a Married 855 (72.3%) 494 (73.7%) 135 (75.0%) 133 (66.5%) 93 (70.5%) Single/ Divorced / Widowed / Separated 80 (27.7%) 176 (26.3%) 45 (25.0%) 67 (33.5%) 39 (29.5%) Living alone <0.001 a Yes 128 (10.8%) 43 (6.4%) 21 (11.7%) 38 (19.0%) 26 (19.7%) No 1,054 (89.2%) 627 (93.6%) 159 (88.3%) 162 (81.0%) 106 (80.3%) Perceived money insufficiency <0.001 a Yes 186 (15.7%) 45 (6.7%) 40 (22.2%) 79 (39.5%) 22 (16.7%) No 996 (84.3%) 625 (93.3%) 140 (77.8%) 121 (60.5%) 110 (83.3%) No. of chronic conditions <0.001 a ≥ 2 388 (32.8%) 159 (23.7%) 71 (39.4%) 109 (54.5%) 49 (37.1%) 0 - 1 794 (67.2%) 511 (76.3%) 109 (60.6%) 91 (45.5%) 83 (62.9%) PHQ-9 score (Mean ± SD Median (IQR)) 1.2 ± 2.4 0 (0 – 1) 0.7 ± 1.4 0 (0 – 1) 1.4 ± 2.8 0 (0 – 2) 2.4 ± 3.7 1 (0 – 3) 1.3 ± 2.2 0 (0 – 2) <0.001 b a P-value derived from Chi-squared test b P-value derived from Kruskal-Wallis H test PHQ-9: Patient Health Questionnaire-9; SD: Standard Deviation; IQR: Interquartile Range Association between changes in social connectedness and subsequent healthcare utilization At baseline, healthcare utilization differed significantly across the four groups in all care settings, with a consistent pattern observed. The group who remained socially disconnected exhibited the highest mean visits, followed by those who became socially disconnected, then those who became socially connected, with those who remained socially connected demonstrating the lowest mean visits (Supplementary File, Table S1 ). In-patient wards After adjusting for baseline covariates (Table 2 ), participants who experienced persistent social disconnection demonstrated significantly higher odds of hospitalization compared to those who remained socially connected. This was observed both in the subsequent year (OR = 2.66, 95% CI: 1.42–4.97, p = 0.002) and at three-year follow-up (OR = 2.11, 95% CI: 1.29–3.43, p = 0.003). Those who became socially connected also demonstrated higher odds of hospitalization than those who remained socially connected at three-year follow-up (OR = 1.88, 95% CI: 1.14–3.10, p = 0.014; IRR = 1.49, 95% CI: 1.06–2.08, p = 0.020). Table 2 Associations of changes in social connection with healthcare utilization at one-year and three-year follow-ups by healthcare settings (in-patient wards, emergency departments, specialist outpatient clinics and polyclinics). Timepoint Healthcare setting Social connection status Yes, n (%) Mean ± SD Median (IQR) Adjusted OR c (95% CI) Adjusted IRR d (95% CI) zero values excluded Subsequent year In-patient wards Remained socially connected (n = 670) 25 (3.7%) 0.1 ± 0.4 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 18 (10.0%) 0.2 ± 0.9 0 (0–0) 1.89 (0.96–3.71) 1.11 (0.69–1.79) Remained socially disconnected (n = 200) 38 (19.0%) 0.4 ± 1.0 0 (0–0) 2.66 (1.42–4.97)** 1.05 (0.65–1.70) Became socially disconnected (n = 132) 11 (8.3%) 0.1 ± 0.5 0 (0–0) 1.66 (0.76–3.62) 0.84 (0.45–1.57) p-value < 0.001 a < 0.001 b Emergency departments Remained socially connected (n = 670) 43 (6.4%) 0.1 ± 0.4 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 31 (17.2%) 0.3 ± 0.9 0 (0–0) 1.94 (1.14–3.32)* 1.36 (0.90–2.04) Remained socially disconnected (n = 200) 44 (22.0%) 0.5 ± 1.2 0 (0–0) 1.72 (1.01–2.94)* 1.38 (0.90–2.12) Became socially disconnected (n = 132) 17 (12.9%) 0.2 ± 0.5 0 (0–0) 1.42 (0.76–2.67) 1.08 (0.65–1.79) p-value < 0.001 < 0.001 Specialist outpatient clinics Remained socially connected (n = 670) 156 (23.3%) 1.3 ± 3.8 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 57 (31.7%) 2.5 ± 8.7 0 (0–2) 1.13 (0.74–1.72) 1.26 (0.94–1.68) Remained socially disconnected (n = 200) 91 (45.5%) 3.1 ± 6.0 0 (0–4) 1.41 (0.93–2.15) 1.05 (0.79–1.38) Became socially disconnected (n = 132) 46 (34.8%) 2.4 ± 5.5 0 (0–2) 1.38 (0.87–2.17) 1.22 (0.89–1.66) p-value < 0.001 < 0.001 Polyclinics Remained socially connected (n = 670) 233 (34.8%) 1.6 ± 3.3 0 (0–2) 1.00 1.00 Became socially connected (n = 180) 66 (36.7%) 1.8 ± 3.3 0 (0–2) 1.04 (0.66–1.62) 0.99 (0.79–1.24) Remained socially disconnected (n = 200) 97 (48.5%) 3.5 ± 9.7 0 (0–5) 1.24 (0.77–1.98) 1.37 (1.12–1.68)** Became socially disconnected (n = 132) 53 (40.2%) 2.5 ± 7.4 0 (0–3) 0.95 (0.58–1.55) 1.24 (0.98–1.56) p-value 0.005 < 0.001 Three years (cumulative) In-patient wards Remained socially connected (n = 670) 21 (3.1%) 0.1 ± 0.6 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 19 (10.6%) 0.5 ± 1.5 0 (0–0) 1.88 (1.14–3.10)* 1.49 (1.06–2.08)* Remained socially disconnected (n = 200) 31 (15.5%) 0.8 ± 1.7 0 (0–1) 2.11 (1.29–3.43)** 1.37 (0.97–1.94) Became socially disconnected (n = 132) 10 (7.6%) 0.3 ± 1.0 0 (0–0) 1.63 (0.91–2.91) 1.14 (0.75–1.74) p-value < 0.001 < 0.001 Emergency departments Remained socially connected (n = 670) 38 (5.7%) 0.3 ± 0.9 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 32 (17.8%) 0.8 ± 1.6 0 (0–1) 2.07 (1.37–3.12)** 1.24 (0.96–1.61) Remained socially disconnected (n = 200) 43 (21.5%) 1.0 ± 2.0 0 (0–1) 1.77 (1.16–2.70)** 1.11 (0.84–1.46) Became socially disconnected (n = 132) 13 (9.8%) 0.5 ± 1.1 0 (0–1) 1.58 (0.99–2.54) 0.98 (0.72–1.35) p-value < 0.001 < 0.001 Specialist outpatient clinics Remained socially connected (n = 670) 150 (22.4%) 3.6 ± 10.0 0 (0–3) 1.00 1.00 Became socially connected (n = 180) 63 (35.0%) 6.8 ± 16.1 0 (0–6) 1.13 (0.76–1.67) 1.25 (0.95–1.65) Remained socially disconnected (n = 200) 86 (43.0%) 8.2 ± 14.4 1.5 (0–11) 1.36 (0.90–2.05) 1.20 (0.92–1.57) Became socially disconnected (n = 132) 40 (30.3%) 6.5 ± 14.0 0 (0–6) 1.33 (0.86–2.04) 1.25 (0.93–1.69) p-value < 0.001 < 0.001 Polyclinics Remained socially connected (n = 670) 232 (34.6%) 4.7 ± 9.2 0 (0–5) 1.00 1.00 Became socially connected (n = 180) 70 (38.9%) 5.6 ± 10.3 1 (0–6) 1.21 (0.81–1.80) 0.90 (0.73–1.11) Remained socially disconnected (n = 200) 85 (42.5%) 8.6 ± 16.8 2 (0–14) 1.02 (0.65–1.59) 1.25 (1.02–1.54)* Became socially disconnected (n = 132) 55 (41.7%) 6.7 ± 11.0 2 (0–9) 1.33 (0.84–2.12) 1.24 (1.00–1.55) p-value 0.131 < 0.001 *p < 0.05 **p < 0.01 SD: Standard deviation; IQR: Interquartile range a Column p-values derived from Chi-squared tests b Column p-values derived from Kruskal-Wallis H tests c Odds Ratio (OR) obtained from logistic regressions, adjusted for the following covariates: baseline visits (yes, no), age group (younger adults, older adults), gender (male, female), ethnicity (Chinese, non-Chinese), education (secondary school & below, post-secondary school & above), employment status (employed, not employed), marital status (married, single/divorced/widowed/separated), living alone (yes, no), perceived money insufficiency for basic living needs (yes, no), number of chronic conditions (0–1, ≥ 2), Patient Health Questionnaire-9 score (integer). d Incidence Rate Ratio (IRR) using generalized linear models with negative binomial distribution or Poisson distribution (for hospitalizations and emergency department visits in the subsequent one year), adjusted for the following covariates: baseline visits (integer), age group (younger adults, older adults), gender (male, female), ethnicity (Chinese, non-Chinese), education (secondary school & below, post-secondary school & above), employment status (employed, not employed), marital status (married, single/divorced/widowed/separated), living alone (yes, no), perceived money insufficiency for basic living needs (yes, no), number of chronic conditions (0–1, ≥ 2), Patient Health Questionnaire-9 score (integer). Emergency departments After adjusting for baseline visits and covariates, those who experienced persistent social disconnection demonstrated significantly higher odds of ED visits both in the subsequent year (OR = 1.72, 95% CI: 1.01–2.94, p = 0.048) and at three-year follow-up (OR = 1.77, 95% CI: 1.16–2.70, p = 0.008) compared to those who remained socially connected. Similarly, those who became socially connected also exhibited higher odds of ED visits compared to those who remained socially connected in the subsequent year (OR = 1.94, 95% CI: 1.14–3.32, p = 0.015) and at three-year follow-up (OR = 2.07, 95% CI: 1.37–3.12, p = 0.001). No significant differences in IRRs were observed across groups. Specialist outpatient clinics No significant associations were observed between changes in social connectedness and subsequent SOC visits at one-year and three-year follow-ups. Polyclinics Compared to those who remained socially connected, the group with persistent social disconnection exhibited higher rates of polyclinic visits in both the subsequent year (IRR = 1.37, 95% CI: 1.12–1.68, p = 0.003) and at three-year follow-up (IRR = 1.25, 95% CI: 1.02–1.54, p = 0.033), controlling for baseline visits and covariates. No significant differences in ORs were observed across groups. Association between changes in social connectedness and subsequent healthcare costs Changes in social connectedness were significantly associated with unadjusted costs for hospitalizations, polyclinic visits, and SOC visits, but not ED visits (Supplementary File, Table S1 ). For the three settings where significant associations were observed, the group who remained socially disconnected exhibited the highest mean cost, followed by those who became socially disconnected, then those who became socially connected, with those who remained socially connected demonstrating the lowest mean cost (Supplementary File, Table S1 ). In-patient wards Individuals who remained socially disconnected demonstrated higher odds of incurring hospitalization costs in the subsequent year (OR = 2.30, 95% CI: 1.21–4.40, p = 0.012) and at three-year follow-up (OR = 1.89, 95% CI: 1.15–3.13, p = 0.013) compared to those who remained socially connected. No significant associations with hospitalization costs were observed for the other groups (Table 3 ). Table 3 Associations of changes in social connection with healthcare cost at one-year and three-year follow-ups by healthcare settings (in-patient wards, emergency departments, specialist outpatient clinics and polyclinics). Timepoint Healthcare setting Isolation/loneliness status Mean ± SD Median (IQR) (SGD) Adjusted OR b (95% CI) Adjusted CR c (95% CI) Zero values excluded Subsequent year In-patient wards Remained socially connected (n = 670) 518 ± 4,555 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 1,360 ± 6,389 0 (0–0) 1.66 (0.83–3.29) 0.84 (0.39–1.78) Remained socially disconnected (n = 200) 2,716 ± 9,598 0 (0–0) 2.30 (1.21–4.40)* 0.63 (0.29–1.34) Became socially disconnected (n = 132) 750 ± 3,338 0 (0–0) 1.28 (0.56–2.90) 0.49 (0.20–1.19) p-value < 0.001 a Emergency departments Remained socially connected (n = 670) 29.70 ± 157 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 132 ± 397 0 (0–0) 1.88 (1.10–3.22)* 1.57 (1.10–2.24)* Remained socially disconnected (n = 200) 192 ± 495 0 (0–0) 1.65 (0.96–2.85) 1.50 (1.03–2.20)* Became socially disconnected (n = 132) 71.6 ± 222 0 (0–0) 1.36 (0.72–2.56) 1.15 (0.77–1.73) p-value < 0.001 Specialist outpatient clinics Remained socially connected (n = 670) 233 ± 846 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 640 ± 2,770 0 (0–214) 1.16 (0.71–1.90) 1.77 (1.08–2.91)* Remained socially disconnected (n = 200) 637 ± 1,583 0 (0–533) 1.63 (1.00–2.64)* 1.07 (0.67–1.69) Became socially disconnected (n = 132) 522 ± 1,459 0 (0–229) 1.67 (0.98–2.83) 0.98 (0.58–1.65) p-value < 0.001 Polyclinics Remained socially connected (n = 670) 181 ± 450 0 (0–115) 1.00 1.00 Became socially connected (n = 180) 258 ± 611 0 (0–172) 1.03 (0.66–1.60) 0.89 (0.68–1.15) Remained socially disconnected (n = 200) 405 ± 687 0 (0–581) 1.33 (0.83–2.11) 1.13 (0.88–1.44) Became socially disconnected (n = 132) 313 ± 850 0 (0–223) 0.93 (0.57–1.52) 1.18 (0.89–1.56) p-value < 0.001 Three years (cumulative) In-patient wards Remained socially connected (n = 670) 1,036 ± 5,450 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 3,413 ± 10,541 0 (0–0) 1.64 (0.90–2.73) 1.32 (0.78–2.21) Remained socially disconnected (n = 200) 6,352 ± 19,399 0 (0–2,094) 1.89 (1.15–3.13)* 1.58 (0.93–2.70) Became socially disconnected (n = 132) 1,940 ± 6,272 0 (0–0) 1.37 (0.75–2.51) 0.80 (0.43–1.49) p-value < 0.001 Emergency departments Remained socially connected (n = 670) 99.70 ± 340 0 (0–0) 1.00 1.00 Became socially connected (n = 180) 343 ± 707 0 (0–422) 1.99 (1.32–3.00)** 1.34 (1.03–1.74)* Remained socially disconnected (n = 200) 413 ± 824 0 (0–515) 1.72 (1.13–2.64)* 1.14 (0.86–1.52) Became socially disconnected (n = 132) 203 ± 454 0 (0–282) 1.56 (0.97–2.51) 0.99 (0.73–1.34) p-value < 0.001 Specialist outpatient clinics Remained socially connected (n = 670) 717 ± 2,469 0 (0–302) 1.00 1.00 Became socially connected (n = 180) 1,486 ± 4,162 0 (0–989) 1.12 (0.73–1.73) 1.51 (0.97–2.36) Remained socially disconnected (n = 200) 1,978 ± 6,945 153 (0–1,580) 1.45 (0.94–2.26) 1.19 (0.77–1.83) Became socially disconnected (n = 132) 1,986 ± 8,416 0 (0–566) 1.54 (0.97–2.46) 1.23 (0.76–1.99) p-value < 0.001 Polyclinics Remained socially connected (n = 670) 554 ± 1,363 0 (0–437) 1.00 1.00 Became socially connected (n = 180) 784 ± 1,877 49.20 (0–538) 1.24 (0.83–1.86) 0.82 (0.63–1.06) Remained socially disconnected (n = 200) 1,144 ± 1,953 115 (0–1,535) 1.07 (0.69–1.67) 1.13 (0.87–1.48) Became socially disconnected (n = 132) 850 ± 1,974 103 (0–808) 1.34 (0.84–2.12) 1.07 (0.80–1.42) p-value < 0.001 * p < 0.05 ** p < 0.01 a Column p-values derived from Kruskal-Wallis H tests b Odds Ratio (OR) obtained from logistic regressions, adjusted for the following covariates: baseline cost (yes, no), age group (younger adults, older adults), gender (male, female), ethnicity (Chinese, non-Chinese), education (secondary school & below, post-secondary school & above), employment status (employed, not employed), marital status (married, single/divorced/widowed/separated), living alone (yes, no), perceived money insufficiency for basic living needs (yes, no), number of chronic conditions (0–1, ≥ 2), Patient Health Questionnaire-9 score (integer). c Cost Ratio (CR) obtained from Gamma regressions, adjusted for the following covariates: baseline cost (numeric), age group (younger adults, older adults), gender (male, female), ethnicity (Chinese, non-Chinese), education (secondary school & below, post-secondary school & above), employment status (employed, not employed), marital status (married, single/divorced/widowed/separated), living alone (yes, no), perceived money insufficiency for basic living needs (yes, no), number of chronic conditions (0–1, ≥ 2), Patient Health Questionnaire-9 score (integer). Emergency departments Compared to those who remained socially connected, individuals who remained socially disconnected exhibited higher cost ratio in the subsequent year (CR = 1.50, 95% CI: 1.03–2.20, p = 0.039) and higher odds ratio at three-year follow-up (OR = 1.72, 95% CI: 1.13–2.64, p = 0.012). Individuals who became socially connected demonstrated higher ED visit costs both in the subsequent year (OR = 1.88, 95% CI: 1.10–3.22, p = 0.021; CR = 1.57, 95% CI: 1.10–2.24, p = 0.014) and at three-year follow-up (OR = 1.99, 95% CI: 1.32-3.00, p = 0.001; CR = 1.34, 95% CI: 1.03–1.74, p = 0.032). Specialist outpatient clinics In the subsequent year, individuals who remained socially disconnected had higher odds of incurring SOC visit costs (OR = 1.63, 95% CI: 1.00-2.64, p = 0.049) while individuals who became socially connected had higher cost ratio (CR = 1.77, 95% CI: 1.09–2.91, p = 0.025) compared to those who remained socially connected. At three-year follow-up, no significant associations were observed between change in social connectedness and cumulative costs incurred across groups. Polyclinics No significant associations were observed between changes in social connectedness and subsequent costs incurred for polyclinic visits across groups at either follow-up. Discussion Main findings This study examined the associations between temporal changes in social connectedness and subsequent one-year and cumulative three-year healthcare utilization as well as cost at four healthcare settings in Singapore. At both time points, persistent social disconnection was associated with increased hospitalizations, polyclinic visits, and ED visits, and higher costs for hospitalizations and ED visits, compared to those who remained socially connected. In addition, it was also associated with higher odds of incurring SOC costs at one-year follow-up. Encouragingly, protective effects were observed for subsequent hospitalizations and polyclinic visits among individuals who became socially connected, although not for ED visits and associated costs. The observations of higher healthcare utilization and costs among the group with persistent social disconnection are aligned with our hypothesis. This could be explained by various pathways through which social isolation and loneliness influence health and healthcare-seeking behaviors. For instance, social disconnection may directly increase healthcare needs through experiences of pain that are disruptive to daily activities 47 or the development of acute health conditions triggered by prolonged stress 48 , 49 . Socially disconnected individuals might also prefer to self-medicate 50 or delay seeking medical care due to contributing factors such as low health literacy 51 , 52 or financial constraints 53 , 54 . Consequently, this avoidant behavior may lead to worsening health conditions that ultimately necessitate emergency care in the longer term 55 . Moreover, the observed effects at three-year follow-up suggest that, while social isolation and loneliness may be transitory states, their health impacts could persist beyond the period of social disconnectedness itself. Contrary to our expectations, however, individuals who became socially disconnected did not exhibit higher subsequent healthcare utilization and costs compared to those who remained socially connected. We posit that this could be due to several factors. First, there may be a lag time between becoming socially disconnected and observable changes in healthcare outcomes, whereby effects may not yet be detectable within our follow-up period. Second, these individuals may have mainly engaged in healthcare avoidant behaviors. It is also plausible that the relatively small sample size of this group (11.2%) may have limited statistical power to detect associations. This warrants further investigation, integrated with qualitative approaches, to better understand the nuances of these observed patterns. In-patient wards This study's findings align with previous research using administrative healthcare data which demonstrated that social disconnection was associated with increased hospital admissions 16 . The protective effects observed among those who became socially connected suggest that interventions aimed at improving social connectedness may help reduce hospitalizations, the most resource-intensive form of care. However, the elevated odds at three-year follow-up raise the possibility that sustained social connectedness may be critical in maintaining these protective effects over time. Potential mechanisms underlying these protective effects include reduced stress-induced adverse health outcomes 48 , improved medication adherence 50 , and engagement in healthier lifestyle choices 56 . Emergency departments Paradoxically, individuals who became socially connected demonstrated higher ED visits and costs at both follow-ups compared to those who remained socially connected, with odds that were even higher than those observed among the group with persistent social disconnection. There are several potential explanations for this counterintuitive observation. It remains unclear whether individuals with apparent improvements subsequently reverted to their socially disconnected status, or whether prior exposure had already impacted their health 57 . It is also possible that these individuals may have experienced extended periods of social disconnection preceding and between data collections, or encountered frequent relapses due to vulnerability from socioeconomic factors 57 . Moreover, as improved social connections may facilitate health-seeking behavior 55 , this could explain why this group exhibited higher urgent care needs than those who remained socially connected, with utilization patterns resembling the persistently socially disconnected group. Last but not least, our analyses only adjusted for the number of chronic conditions, while disease severity could have been a stronger mediator of healthcare utilization and costs. These patterns suggest that the healthcare impacts of social disconnectedness may persist even after social circumstances improve, highlighting the importance of early intervention and prevention strategies. Specialist outpatient clinics This study addresses an understudied area in the literature regarding the association of social disconnectedness with outpatient specialist consultations. While SOC visit frequency did not differ by groups after adjusting for baseline visits and covariates such as multimorbidity, persistently socially disconnected individuals displayed higher odds of incurring SOC costs at one-year follow-up. Among those who incurred SOC costs, individuals who became socially connected demonstrated higher cost ratios at one-year but not three-year follow-up. The lack of significant associations with visit frequency, despite differences in costs, suggests that these two groups might have presented with more complex care needs requiring costlier specialist care in the shorter term. Polyclinics Compared to those who remained socially connected, the group with persistent social disconnection exhibited higher rates of polyclinic visits at both one-year and three-year follow-ups after controlling for baseline visits and covariates. As polyclinics cater to a sizeable patient population with chronic conditions by providing a comprehensive range of services at subsidized rates in Singapore 58 , the sustained higher utilization among persistently disconnected polyclinic attendees may reflect ongoing management of chronic health conditions that could have been exacerbated by social disconnectedness. Encouragingly, individuals who became socially connected did not demonstrate higher polyclinic utilization, compared to those who remained socially connected at either follow-up, suggesting protective effects similar to that observed for hospitalizations. This finding that strengthening social ties may help reduce the burden on primary care services is particularly noteworthy for Singapore's healthcare system, where polyclinics are already experiencing significant resource constraints from high patient volumes 58 . Strengths and Limitations To the best of our knowledge, this is the first study in Singapore to examine social isolation, loneliness, and their effects on subsequent healthcare utilization and cost using administrative data from multiple care settings, providing insights specific to Singapore's unique sociocultural context. The advantages of utilizing administrative data include mitigating potential recall bias and enhancing the detection of effects 59 . Furthermore, the prospective analysis approach minimizes possible reverse causality, whereby healthcare utilization might have contributed to changes in social connectedness. However, this study combined social isolation and loneliness into the broader concept of social disconnection, which carries the assumption that both constructs have equivalent impacts on healthcare utilization and cost outcomes. Although ideally these constructs would be examined separately, differentiating their individual effects was not within the scope of this study due to the small sample sizes of the groups with changes in social connectedness, which were reduced further when investigating utilization by healthcare setting. Additionally, while holding covariates constant at baseline values enhanced interpretability of results, potential changes in time-varying sociodemographic factors that may influence social isolation and loneliness status were not accounted for. We also could not account for potential fluctuations in social connectedness between measurement points, and the lag time between changes in social connectedness and health outcomes may mean that some effects might not be detectable within our follow-up period. Finally, this study was limited to participants with healthcare utilization and cost records at NHG Health institutions. This exclusion of individuals who did not utilize NHG Health’s services may introduce selection bias, affect generalizability, and underestimate the total healthcare utilization and costs for those who sought care from other healthcare providers. Implications and future directions As Singapore works to meet rising healthcare demands from a rapidly aging population seeks to keep costs contained 58 , our results suggest that interventions targeting social connectedness could yield cost savings and ease resource strain across multiple healthcare settings. The protective effects observed for those who became socially connected suggest that social prescribing initiatives and community-based interventions could be cost-effective strategies for reducing healthcare burden. Among those who remained socially disconnected, there was a higher proportion of older adults (62.0%), underscoring the vulnerability of this demographic. In Singapore, there has been an active push to promote social engagement and community integration among the older adult population. For instance, the national Age Well SG program, launched in 2023, has various community initiatives to engage, encourage and enable seniors to keep physically and socially active 60 . Such community programs that promote social connections through group activities or volunteer opportunities can help to reduce feelings of loneliness and improve health outcomes 61 . Additionally, there are continual outreach efforts to older adults who may be socially isolated by the Silver Generation Office, the senior engagement arm of the Agency for Integrated Care that was established by the Ministry of Health Singapore 62 . In light of these efforts, future studies could not only evaluate the effectiveness of existing initiatives in addressing social isolation and loneliness, but also assess the individual and collective impacts on healthcare utilization and associated costs using population-representative administrative data. Building upon our findings of consistent associations between social disconnectedness and subsequent hospitalizations in Singapore's context, future research may also examine more granular utilization outcomes such as the length of stay and types of hospitalizations. For instance, Christiansen et al. (2023) observed that loneliness was linked to longer hospital stays in the Danish general population 17 , and Molloy et al. (2010) noted that loneliness was associated with unplanned hospitalizations but not planned admissions among community-dwelling adults in Ireland 63 . Where sample sizes permit, studies could investigate the associations of social isolation and loneliness with healthcare utilization separately to ascertain whether there are differential patterns of effects 64 . Evidence from these studies would provide valuable insights to inform the refinement of targeted interventions as well as healthcare policy decisions. Finally, these findings underscore the importance of addressing social connectedness as a modifiable determinant of healthcare utilization. Policymakers may consider integrating social connectedness screening and interventions into Singapore's broader health strategies, such as Healthier SG, which emphasizes preventive care and population health management. Given that screening tools for social isolation and loneliness require minimal cost and time to implement, healthcare stakeholders may consider the systematic implementation of such screening tools to identify high-risk individuals, as well as enhanced integration of social support services and therapeutic interventions within healthcare delivery systems. These strategies would facilitate timely intervention and potentially reduce the burden on healthcare utilization and associated costs, particularly hospitalizations. For instance, individuals may require referral to structured interventions such as cognitive-behavioral therapy to alleviate feelings of loneliness if community activities are less effective for their needs 65 . However, it should be noted that these strategies might shift healthcare utilization patterns rather than decrease them overall. For example, if primary care professionals were to be the first line of screening and intervention for social isolation and loneliness, utilization may increase in this setting 66 . Insights from qualitative studies could therefore illuminate the acceptability and feasibility of addressing social disconnectedness in clinical and community settings within Singapore's context, as older people may view loneliness as a personal problem and demonstrate resistance towards addressing it in primary care settings 67 . Conclusion Persistent social disconnection was associated with higher healthcare utilization and costs across multiple healthcare settings compared to those who remained socially connected. While becoming socially connected demonstrated protective effects for subsequent hospitalizations and polyclinic visits, this group consistently demonstrated higher ED visits and costs at both one-year and three-year follow-ups, which warrants further research to elucidate the underlying mechanisms, including whether improved social connections facilitate earlier urgent care-seeking behavior or reflect persistent health vulnerabilities from prior social disconnection. No significant associations with healthcare utilization and costs were observed for those who became socially disconnected across all care settings. These findings suggest that proactive approaches to maintain or improve social connections, particularly among older adults who comprised the majority of those persistently socially disconnected, may help ease healthcare resource strains and yield cost savings by reducing hospitalizations, which are costly to healthcare and economic systems. Declarations Competing interests The authors declare no competing interests. Ethics declaration The PHI study was approved by the ethics review committee of the National Healthcare Group Domain Specific Review Board (Reference Number: 2015/00269). Written informed consent was obtained from all individual participants after they were being informed about the study objectives and the safeguards put in place so that confidentiality of the collected data is maintained. Funding This work did not receive any external funding support. All authors were employees of the National Healthcare Group Pte Ltd. However, the employer had no role in / influence on study design, data collection and analysis, result interpretation, decision to publish, or preparation of the manuscript. Author Contribution G.H. analyzed and interpreted the data, drafted the initial manuscript, and made subsequent revisions. C.W.Y. interpreted the data and reviewed the article. 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Reform. 5 , 18–23. https://doi.org/10.1080/23288604.2018.1543830 (2019). Sirois, F. M. & Owens, J. A meta-analysis of loneliness and use of primary health care. Health Psychol. Rev. 17 , 193–210. https://doi.org/10.1080/17437199.2021.1986417 (2023). SG, A. W. What is Age Well SG? < (2025). https://www.agewellsg.gov.sg/about/ Toepoel, V., Ageing, Leisure & Connectedness, S. How could Leisure Help Reduce Social Isolation of Older People? Soc. Indic. Res. 113 , 355–372. https://doi.org/10.1007/s11205-012-0097-6 (2013). Care, A. & f., I. About SGO , (2025). https://www.aic.sg/community/about-sgo/ Molloy, G. J., McGee, H. M., O'Neill, D. & Conroy, R. M. Loneliness and Emergency and Planned Hospitalizations in a Community Sample of Older Adults. J. Am. Geriatr. Soc. 58 , 1538–1541. https://doi.org/https://doi.org/10.1111/j.1532-5415.2010.02960.x (2010). Gao, Q., Mak, H. W. & Fancourt, D. Longitudinal associations between loneliness, social isolation, and healthcare utilisation trajectories: a latent growth curve analysis. Soc. Psychiatry Psychiatr. Epidemiol. 59 , 1839–1848. https://doi.org/10.1007/s00127-024-02639-9 (2024). Smith, R., Wuthrich, V., Johnco, C. & Belcher, J. Effect of Group Cognitive Behavioural Therapy on Loneliness in a Community Sample of Older Adults: A Secondary Analysis of a Randomized Controlled Trial. Clin. Gerontologist . 44 , 439–449. https://doi.org/10.1080/07317115.2020.1836105 (2021). Galvez-Hernandez, P., González-de Paz, L. & Muntaner, C. Primary care-based interventions addressing social isolation and loneliness in older people: a scoping review. BMJ Open. 12 , e057729. https://doi.org/10.1136/bmjopen-2021-057729 (2022). Kharicha, K. et al. What do older people experiencing loneliness think about primary care or community based interventions to reduce loneliness? A qualitative study in England. Health Soc. Care Commun. 25 , 1733–1742. https://doi.org/https://doi.org/10.1111/hsc.12438 (2017). Additional Declarations No competing interests reported. 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1","display":"","copyAsset":false,"role":"figure","size":111374,"visible":true,"origin":"","legend":"\u003cp\u003eSelection process of study participants.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8402329/v1/8e58700ca01d00d90b4d93ab.png"},{"id":100399370,"identity":"81608f7e-9ff9-4b8d-9f04-34bf70cd8bc6","added_by":"auto","created_at":"2026-01-16 11:56:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3475279,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8402329/v1/844d7073-06ed-4f63-8e20-808fcb3777a1.pdf"},{"id":100388554,"identity":"d9d62ea7-d0c9-4350-96d7-e64d88ec823b","added_by":"auto","created_at":"2026-01-16 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These distinct social phenomena are growing concerns in large, industrialized societies which have become increasingly fragmented due to a multitude of factors, including urbanization and shifts towards an aging population as well as nuclear family structures \u003csup\u003e\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. In 2025, the World Health Organization Commission on Social Connection issued a landmark report recognizing social isolation and loneliness as pressing public health challenges in many countries and urging policymakers and stakeholders to prioritize interventions addressing these issues \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. A national online survey in the United States reported that the proportion of adults experiencing loneliness has been trending upwards, from 46% in 2018 to 58% in 2023 \u003csup\u003e7\u003c/sup\u003e, and a survey among European Union countries found that over 35% of respondents had experienced loneliness at least sometimes in 2022 \u003csup\u003e8\u003c/sup\u003e. There were similar observations in developed Asian countries, with loneliness estimated to be affecting approximately one-third of the general population in Korea and Japan \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. On social isolation, research has focused primarily on older adults, with a meta-analysis of 41 studies by Teo et al. (2023) revealing a pooled global prevalence of 25% in this demographic \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSocial isolation and loneliness are critical social determinants of health, associated with profound detrimental effects on both physical and mental health outcomes, including elevated risk of premature mortality \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, increased severity of depression \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, and greater susceptibility to unhealthy behaviors \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, which could contribute to increased healthcare needs and utilization. Investigations into the relationships between social isolation, loneliness, and healthcare utilization have yielded mixed findings, with results varying by study design and outcome measurement approach. Studies utilizing administrative data have consistently found associations with increased hospitalizations \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, emergency department (ED) visits \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and general practitioner (GP) visits \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, studies relying on self-reported healthcare utilization have produced more variable results, with some noting increased hospitalizations \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, ED visits \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, and GP visits \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, while others found no significant associations with hospitalizations \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and primary care use \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. These mixed findings suggest there may be multiple competing mechanisms, with some being more influential depending on factors such as the population studied, healthcare system characteristics, and research study approaches. Beyond healthcare demand and resource allocation challenges, social isolation and loneliness also impose substantial economic burdens. For instance, Mira et al. (2024) observed that lonely older adults incurred \u0026euro;802.18 more in healthcare costs annually compared to those who were socially connected \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn Singapore, several key demographic trends \u0026ndash; an ageing population, rising proportion of singles, and more individuals living alone \u0026ndash; could have contributed to the growing prevalence of social isolation and loneliness \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. As individuals age, they may be more susceptible to social isolation and loneliness as their social network size reduces or when they encounter adverse life events such as unemployment or the development of disabilities \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Moreover, as a metropolitan city undergoing digital transformation, Singapore faces another layer of complexity in social connection patterns. The rapid digitalization and integration of technologies and social media in daily life present a double-edged sword: although digital platforms and solutions may offer promising opportunities to enhance social connectivity, particularly for vulnerable populations such as older adults with limited mobility, maladaptive use could paradoxically exacerbate social isolation and loneliness by reducing in-person, meaningful interactions and authentic relationships \u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGiven these key population trends and the dynamic nature of social isolation and loneliness, it is important to better understand the effects of changes in social disconnection on healthcare utilization as this can reveal critical windows for healthcare planning and intervention design. Lim \u0026amp; Chan (2017) observed that persistently lonely older adults were less likely to use primary care services in the past month based on self-reported data \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, but no local study has examined how changes in both social isolation and loneliness status affect subsequent healthcare utilization and in the longer term. Importantly, social isolation and loneliness share common risk factors, such as living alone and being widowed or divorced \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, and evidence suggests that both should be addressed concurrently to achieve marked improvements in overall health and wellbeing \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This present study examines social isolation and loneliness together under the broader concept of social connectedness to assess its impact on healthcare utilization and cost outcomes.\u003c/p\u003e \u003cp\u003eThe primary study objective is to investigate the associations of temporal changes in social connectedness with subsequent healthcare utilization and cost among the adult population in Singapore in four care settings: in-patient wards, EDs, specialist outpatient clinics (SOCs), and polyclinics. Specifically, this study seeks to address two research questions:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhat are the associations of changes in social connectedness with healthcare utilization patterns in different care settings at one-year and three-year follow-ups?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWhat are the associations of changes in social connectedness with gross healthcare cost in different care settings at one-year and three-year follow-ups?\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eCompared to those who remained socially connected, our hypotheses are:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eIndividuals with persistent social disconnection will exhibit significantly higher healthcare utilization and associated costs in the respective care settings at both follow-ups.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIndividuals with transient social disconnection will demonstrate higher healthcare utilization and associated cost in the respective care settings at both follow-ups, albeit to a lesser extent than those with persistent social disconnection.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eData were derived from the first two waves of the Population Health Index (PHI) Study Phase 1, conducted annually in 2015 and 2016, which comprised a random sample of Singapore citizens and permanent residents aged 21 years and above residing in the Central region. The development of the PHI survey instruments, stratified sampling methodology, and data collection procedures have been detailed elsewhere \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The PHI study received ethical approval from the National Healthcare Group Domain Specific Review Board (Reference Number: 2015/00269). All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e \u003cp\u003eA total of 1,942 adults completed the first survey (response rate of 53.3%), of whom 1,704 (87.7%) provided additional consent to link their survey responses with administrative databases for research purposes. For individuals who consented, their PHI survey responses were linked with healthcare utilization data extracted from the institution\u0026rsquo;s central data repository. Participants were excluded if they: 1) had missing social isolation or loneliness scores in either survey, or 2) were not NHG Health patients. This resulted in a final sample of 1,182 for analysis. The participant selection process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSocial isolation\u003c/h2\u003e \u003cp\u003eSocial isolation was assessed using the Lubben Social Network Scale-6 (LSNS-6), a validated instrument that measures social connectedness \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. The scale comprises two subscales (family and friend), with three questions each, scored on a 6-point Likert scale ranging from 0 (none) to 5 (nine or more): 0\u0026thinsp;=\u0026thinsp;0, 1\u0026thinsp;=\u0026thinsp;1, 2\u0026thinsp;=\u0026thinsp;2, 3\u0026thinsp;=\u0026thinsp;3\u0026ndash;4, 4\u0026thinsp;=\u0026thinsp;5\u0026ndash;8, 5\u0026thinsp;=\u0026thinsp;\u0026ge;\u0026thinsp;9. The six questions were: 1) \u0026ldquo;How many [relatives/friends] do you see/hear from at least once a month?\u0026rdquo;, 2) \u0026ldquo;How many [relatives/friends] do you feel at ease with whom you can talk about private matters?\u0026rdquo;, and 3) \u0026ldquo;How many [relatives/friends] do you feel close to such that you could call on them for help?\u0026rdquo;. The scale demonstrated good internal consistency in this study (Cronbach's alpha\u0026thinsp;=\u0026thinsp;0.80 for the overall scale; 0.80 and 0.81 for the family and friend subscales respectively). The total score (range: 0\u0026ndash;36) was calculated by summing up all six item scores. Following established thresholds, participants were categorized as socially isolated if the total score ranged between 0\u0026ndash;12 \u003csup\u003e35\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLoneliness\u003c/h3\u003e\n\u003cp\u003eLoneliness was assessed using the University of California Los Angeles (UCLA) Loneliness Scale consisting of three questions: 1) \u0026ldquo;How often do you feel that you lack companionship?\u0026rdquo;, 2) \u0026ldquo;How often do you feel left out?\u0026rdquo;, and 3) \u0026ldquo;How often do you feel isolated from others?\u0026rdquo; \u003csup\u003e36\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEach question has three frequency-related response options: 1\u0026thinsp;=\u0026thinsp;Hardly ever, 2\u0026thinsp;=\u0026thinsp;Some of the time, 3\u0026thinsp;=\u0026thinsp;Often. The scale demonstrated good overall internal reliability in this study (Cronbach\u0026rsquo;s alpha\u0026thinsp;=\u0026thinsp;0.87). The total score (range: 0\u0026ndash;9) was calculated by summing up all three item scores. Based on the summed scores, participants were categorized as either lonely (total score: 6\u0026ndash;9) or not lonely (total score: 3\u0026ndash;5) \u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eChange in social connectedness\u003c/h3\u003e\n\u003cp\u003eFirst, a binary variable for social connectedness was created to classify participants as either socially connected (not isolated and not lonely, coded as 0) or socially disconnected (socially isolated and/or lonely, coded as 1) for each time point. Thereafter, this study\u0026rsquo;s independent variable, a four-level categorical variable, was constructed to capture temporal changes in social connectedness between the first and follow-up surveys: remained socially connected (socially connected in both surveys, coded as 0), became socially connected (socially disconnected in the first survey but socially connected at follow-up survey, coded as 1), remained socially disconnected (socially disconnected in both surveys, coded as 2), and became socially disconnected (socially connected in the first survey but socially disconnected at follow-up survey, coded as 3).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHealthcare utilization and cost\u003c/h2\u003e \u003cp\u003eHealthcare utilization and gross cost across four care settings (inpatient wards, EDs, SOCs, and polyclinics) were extracted for three time points: one year prior to the first survey (establishing the baseline healthcare utilization and cost), one year after the follow-up survey, and three years after the follow-up survey (cumulative).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eWe also extracted baseline socio-demographic factors including age group (younger adults\u0026thinsp;\u0026lt;\u0026thinsp;60 years, older adults\u0026thinsp;\u0026ge;\u0026thinsp;60 years), sex (male, female), ethnicity (Chinese, non-Chinese), education (post-secondary school \u0026amp; above, secondary school \u0026amp; below), employment status (employed, not employed), marital status (married, single / divorced / widowed/ separated), living alone (yes, no), and perceived money insufficiency for basic living needs (yes, no); health-related data included number of chronic conditions (0\u0026ndash;1, \u0026ge;\u0026thinsp;2) out of a list of 17 conditions \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e and depressive symptoms measured using the Patient Health Questionnaire-9 (PHQ-9) \u003csup\u003e39\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMulticollinearity among covariates was assessed using Variance Inflation Factors (VIF). With all adjusted generalized VIF values below 2, there are no significant multicollinearity concerns \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eSample size calculation\u003c/h3\u003e\n\u003cp\u003eTo determine the minimum required sample size, the following formula for regression analyses, with an assumption of a medium effect size (significance level of 5% and statistical power of 80%) between the independent variables (IVs) and dependent variable (DV), was utilized: N\u0026thinsp;\u0026ge;\u0026thinsp;50\u0026thinsp;+\u0026thinsp;8\u003cem\u003em\u003c/em\u003e, where \u003cem\u003em\u003c/em\u003e is the number of IVs in the model \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor this approach, each level of a categorical variable would be counted as one IV \u003csup\u003e42\u003c/sup\u003e. For instance, the continuous PHQ-9 variable is one IV while the categorical change in social connectedness variable with four levels would be counted as four IVs. With 23 IVs in total, the minimum sample size required was 234 (50 + (8 x 23)\u0026thinsp;=\u0026thinsp;234). This study\u0026rsquo;s sample of 1,182 participants is therefore adequate.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDemographics and covariates from the first survey formed the baseline and were summarized for the overall study population and by changes in social connectedness. Categorical variables were presented as frequencies and percentages, while continuous variables were described using means and standard deviations (SD). For categorical variables, between-group differences were assessed using Chi-squared tests. As the continuous variables in this study follow non-normal distributions, both mean [SD] and median [interquartile range (IQR)] were reported, and non-parametric Kruskal-Wallis H tests were used for comparison across groups.\u003c/p\u003e \u003cp\u003eHealthcare utilization and costs were analyzed separately for each care setting as the dependent variable at two timepoints: one year and three years (cumulative) following the completion of the follow-up survey. Given the excess zeros and right-skewed distribution characteristic of healthcare utilization data, a two-step hurdle model was selected for the analyses of both healthcare utilization and costs \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFor healthcare utilization, healthcare visits were first dichotomized (0: no visits; 1: \u0026ge;1 visit), and logistic regressions were conducted, controlling for baseline utilization and covariates. The coefficients were exponentiated, and results were presented as odds ratios (OR) with 95% confidence intervals (CIs). In the second step, participants with zero utilization were excluded, and a generalized linear model (GLM) with Poisson distribution was fitted. Testing for overdispersion was then performed to detect potential violation of the Poisson model assumption of equal mean-variance relationship that could lead to inflated Type 1 error rates in hypothesis testing \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Overdispersion was assessed using the \u003cem\u003eperformance\u003c/em\u003e package and \u003cem\u003echeck overdispersion\u003c/em\u003e function in R Studio \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Values more than 1 would indicate that the variance is larger than the mean, and a p-value of \u0026lt;\u0026thinsp;0.05 would suggest that the overdispersion is significant and the Poisson model assumption is violated. For hospitalizations and ED visits in the subsequent one year, no overdispersion was detected and analysis was conducted using Poisson GLMs. For the other care settings and in the cumulative third year, overdispersion was detected and negative binomial GLMs were employed instead. The coefficients were exponentiated, and results were expressed as incidence rate ratios (IRR) with 95% CIs.\u003c/p\u003e \u003cp\u003eSimilarly, for the first step, healthcare costs were dichotomized (0: no cost incurred; 1: cost incurred) and logistic regressions were conducted, controlling for baseline cost and covariates. Coefficients were exponentiated and results were presented as ORs with 95% CIs. In the second step, GLM regression with Gamma distribution and log link was employed to account for the typically right-skewed distribution of cost data among users, controlling for baseline covariates. Coefficients were exponentiated, and results were expressed as cost ratios (CR) with 95% CIs.\u003c/p\u003e \u003cp\u003eAll analyses were conducted using R Studio version 4.5.0, with statistical significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003eBaseline characteristics\u003c/h2\u003e\n\u003cp\u003eThe majority of the 1,182 participants were younger adults (61.3%), female (55.0%), of Chinese ethnicity (78.8%), attained post-secondary school education (40.9%), employed (60.7%), married (72.3%), not living alone (89.2%), had perceived money sufficiency (84.3%), and no chronic conditions (67.2%).\u003c/p\u003e\n\u003cp\u003eBetween the first and follow-up surveys, approximately 3 in 10 participants experienced changes in social connectedness. A slightly higher proportion became socially connected (15.2%) compared to those who became socially disconnected (11.2%). More than half of the participants (56.7%) remained socially connected, while 16.9% were persistently socially disconnected. The persistently socially disconnected group was predominantly older adults (62.0%), had secondary school education or below (87.0%), were not employed (61.5%), reported perceived money insufficiency (39.5%), and had multiple chronic conditions (54.5%). Mean PHQ-9 score was the highest in the persistently isolated and/or lonely group (Mean\u0026thinsp;=\u0026thinsp;2.4, SD\u0026thinsp;=\u0026thinsp;3.7) and the lowest among those who remained socially connected (Mean\u0026thinsp;=\u0026thinsp;0.7, SD\u0026thinsp;=\u0026thinsp;1.4). Detailed participant characteristics at baseline are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBaseline characteristics of study participants by changes in social connection (n\u0026thinsp;=\u0026thinsp;1,182).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(n=1,182)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(n=670, 56.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(n=180, 15.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e\u003cstrong\u003e n (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(n=200, 16.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003en (%)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(n=132, 11.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge \u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Younger adults\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; (\u0026lt; 60 years old)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e725 (61.3%)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e468 (69.9%)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e99 (55.0%)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e76 (38.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e82 (62.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Older adults\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; (\u0026ge; 60 years old)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e457 (38.7%)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e202 (30.1%)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e81 (45.0%)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e124 (62.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e50 (37.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Female\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e650 (55.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e367 (54.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e108 (60.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e112 (56.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e63 (47.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Male\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e532 (45.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e303 (45.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e72 (40.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e88 (44.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e69 (52.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e0.126\u003csup\u003e a\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Chinese\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e932 (78.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e530 (79.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e137 (76.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e158 (79.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e107 (81.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Non-Chinese\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e250 (21.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e140 (20.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e43 (23.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e42 (21.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e25 (18.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eHighest education attained\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003csup\u003e a\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Post-secondary\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; school \u0026amp; above\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e484 (40.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e366 (54.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e53 (29.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e26 (13.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e39 (29.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Secondary\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; school \u0026amp; below\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e698 (59.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e304 (45.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e127 (70.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e174 (87.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e93 (70.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eEmployment status\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003csup\u003e a\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Employed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e717 (60.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e455 (67.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e107 (59.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e77 (38.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e78 (59.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Not employed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e465 (39.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e215 (32.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e73 (40.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e123 (61.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e54 (40.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003csup\u003e a\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Married\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e855 (72.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e494 (73.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e135 (75.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e133 (66.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e93 (70.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Single/ Divorced\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; / Widowed /\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Separated\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e80 (27.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e176 (26.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e45 (25.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e67 (33.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e39 (29.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eLiving alone\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001 \u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e128 (10.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e43 (6.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e21 (11.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e38 (19.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e26 (19.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; No\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e1,054 (89.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e627 (93.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e159 (88.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e162 (81.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e106 (80.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003ePerceived money insufficiency\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003csup\u003e a\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; Yes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e186 (15.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e45 (6.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e40 (22.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e79 (39.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e22 (16.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; No\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e996 (84.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e625 (93.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e140 (77.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e121 (60.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e110 (83.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003eNo. of chronic conditions\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003csup\u003e a\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; \u0026ge; 2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e388 (32.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e159 (23.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e71 (39.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e109 (54.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e49 (37.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; 0 - 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e794 (67.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e511 (76.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e109 (60.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e91 (45.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e83 (62.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"132\"\u003e\n\u003cp\u003e\u003cstrong\u003ePHQ-9 score \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(Mean \u003c/strong\u003e\u0026plusmn; \u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMedian (IQR))\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e1.2 \u0026plusmn; 2.4\u003c/p\u003e\n\u003cp\u003e0 (0 \u0026ndash; 1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.7 \u0026plusmn; 1.4\u003c/p\u003e\n\u003cp\u003e0 (0 \u0026ndash; 1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e1.4 \u0026plusmn; 2.8\u003c/p\u003e\n\u003cp\u003e0 (0 \u0026ndash; 2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2.4 \u0026plusmn; 3.7\u003c/p\u003e\n\u003cp\u003e1 (0 \u0026ndash; 3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"104\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.3 \u0026plusmn; 2.2\u003c/p\u003e\n\u003cp\u003e0 (0 \u0026ndash; 2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003csup\u003e b\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea \u003c/sup\u003e\u003cem\u003eP-value derived from Chi-squared test\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003eb \u003c/sup\u003e\u003c/em\u003e\u003cem\u003eP-value derived from Kruskal-Wallis H test\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePHQ-9: Patient Health Questionnaire-9; SD: Standard Deviation; IQR: Interquartile Range\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003eAssociation between changes in social connectedness and subsequent healthcare utilization\u003c/h2\u003e\n\u003cp\u003eAt baseline, healthcare utilization differed significantly across the four groups in all care settings, with a consistent pattern observed. The group who remained socially disconnected exhibited the highest mean visits, followed by those who became socially disconnected, then those who became socially connected, with those who remained socially connected demonstrating the lowest mean visits (Supplementary File, Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n\u003ch2\u003eIn-patient wards\u003c/h2\u003e\n\u003cp\u003eAfter adjusting for baseline covariates (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), participants who experienced persistent social disconnection demonstrated significantly higher odds of hospitalization compared to those who remained socially connected. This was observed both in the subsequent year (OR\u0026thinsp;=\u0026thinsp;2.66, 95% CI: 1.42\u0026ndash;4.97, p\u0026thinsp;=\u0026thinsp;0.002) and at three-year follow-up (OR\u0026thinsp;=\u0026thinsp;2.11, 95% CI: 1.29\u0026ndash;3.43, p\u0026thinsp;=\u0026thinsp;0.003). Those who became socially connected also demonstrated higher odds of hospitalization than those who remained socially connected at three-year follow-up (OR\u0026thinsp;=\u0026thinsp;1.88, 95% CI: 1.14\u0026ndash;3.10, p\u0026thinsp;=\u0026thinsp;0.014; IRR\u0026thinsp;=\u0026thinsp;1.49, 95% CI: 1.06\u0026ndash;2.08, p\u0026thinsp;=\u0026thinsp;0.020).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAssociations of changes in social connection with healthcare utilization at one-year and three-year follow-ups by healthcare settings (in-patient wards, emergency departments, specialist outpatient clinics and polyclinics).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTimepoint\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eHealthcare setting\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSocial connection status\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eYes, n (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n\u003cp\u003eMedian (IQR)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAdjusted OR \u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAdjusted IRR \u003csup\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(95% CI)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ezero values excluded\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"16\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSubsequent year\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eIn-patient wards\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003cp\u003e(3.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003cp\u003e(10.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.89 (0.96\u0026ndash;3.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.11 (0.69\u0026ndash;1.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003cp\u003e(19.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.66 (1.42\u0026ndash;4.97)**\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.05 (0.65\u0026ndash;1.70)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003cp\u003e(8.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.1 \u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.66 (0.76\u0026ndash;3.62)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.84 (0.45\u0026ndash;1.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEmergency departments\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003cp\u003e(6.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003cp\u003e(17.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.94 (1.14\u0026ndash;3.32)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.36 (0.90\u0026ndash;2.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44\u003c/p\u003e\n\u003cp\u003e(22.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.72 (1.01\u0026ndash;2.94)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.38 (0.90\u0026ndash;2.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003cp\u003e(12.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.42 (0.76\u0026ndash;2.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.08 (0.65\u0026ndash;1.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSpecialist outpatient clinics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e156\u003c/p\u003e\n\u003cp\u003e(23.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003cp\u003e(31.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.13 (0.74\u0026ndash;1.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.26 (0.94\u0026ndash;1.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e91\u003c/p\u003e\n\u003cp\u003e(45.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.0\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.41 (0.93\u0026ndash;2.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.05 (0.79\u0026ndash;1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46\u003c/p\u003e\n\u003cp\u003e(34.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.38 (0.87\u0026ndash;2.17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.22 (0.89\u0026ndash;1.66)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePolyclinics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e233\u003c/p\u003e\n\u003cp\u003e(34.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003cp\u003e(36.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.04 (0.66\u0026ndash;1.62)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.99 (0.79\u0026ndash;1.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97\u003c/p\u003e\n\u003cp\u003e(48.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.24 (0.77\u0026ndash;1.98)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.37 (1.12\u0026ndash;1.68)**\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e53\u003c/p\u003e\n\u003cp\u003e(40.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.95 (0.58\u0026ndash;1.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.24 (0.98\u0026ndash;1.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e0.005\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"16\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eThree years (cumulative)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eIn-patient wards\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003cp\u003e(3.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003cp\u003e(10.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.88 (1.14\u0026ndash;3.10)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.49 (1.06\u0026ndash;2.08)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003cp\u003e(15.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.11 (1.29\u0026ndash;3.43)**\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.37 (0.97\u0026ndash;1.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003cp\u003e(7.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.63 (0.91\u0026ndash;2.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.14 (0.75\u0026ndash;1.74)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEmergency departments\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38\u003c/p\u003e\n\u003cp\u003e(5.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003cp\u003e(17.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.07 (1.37\u0026ndash;3.12)**\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.24 (0.96\u0026ndash;1.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003cp\u003e(21.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.77 (1.16\u0026ndash;2.70)**\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.11 (0.84\u0026ndash;1.46)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003cp\u003e(9.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.58 (0.99\u0026ndash;2.54)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.98 (0.72\u0026ndash;1.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSpecialist outpatient clinics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e150\u003c/p\u003e\n\u003cp\u003e(22.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e63\u003c/p\u003e\n\u003cp\u003e(35.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.13 (0.76\u0026ndash;1.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.25 (0.95\u0026ndash;1.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e86\u003c/p\u003e\n\u003cp\u003e(43.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4\u003c/p\u003e\n\u003cp\u003e1.5 (0\u0026ndash;11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.36 (0.90\u0026ndash;2.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.20 (0.92\u0026ndash;1.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003cp\u003e(30.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.33 (0.86\u0026ndash;2.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.25 (0.93\u0026ndash;1.69)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePolyclinics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e232\u003c/p\u003e\n\u003cp\u003e(34.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003cp\u003e(38.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/p\u003e\n\u003cp\u003e1 (0\u0026ndash;6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.21 (0.81\u0026ndash;1.80)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.90 (0.73\u0026ndash;1.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e85\u003c/p\u003e\n\u003cp\u003e(42.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;16.8\u003c/p\u003e\n\u003cp\u003e2 (0\u0026ndash;14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.02 (0.65\u0026ndash;1.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.25 (1.02\u0026ndash;1.54)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55\u003c/p\u003e\n\u003cp\u003e(41.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e\n\u003cp\u003e2 (0\u0026ndash;9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.33 (0.84\u0026ndash;2.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.24 (1.00\u0026ndash;1.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e0.131\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003e\u003cem\u003e*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003e\u003cem\u003eSD: Standard deviation; IQR: Interquartile range\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eColumn p-values derived from Chi-squared tests\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eColumn p-values derived from Kruskal-Wallis H tests\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eOdds Ratio (OR) obtained from logistic regressions, adjusted for the following covariates: baseline visits (yes, no), age group (younger adults, older adults), gender (male, female), ethnicity (Chinese, non-Chinese), education (secondary school \u0026amp; below, post-secondary school \u0026amp; above), employment status (employed, not employed), marital status (married, single/divorced/widowed/separated), living alone (yes, no), perceived money insufficiency for basic living needs (yes, no), number of chronic conditions (0\u0026ndash;1, \u0026ge;\u0026thinsp;2), Patient Health Questionnaire-9 score (integer).\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cem\u003ed\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eIncidence Rate Ratio (IRR) using generalized linear models with negative binomial distribution or Poisson distribution (for hospitalizations and emergency department visits in the subsequent one year), adjusted for the following covariates: baseline visits (integer), age group (younger adults, older adults), gender (male, female), ethnicity (Chinese, non-Chinese), education (secondary school \u0026amp; below, post-secondary school \u0026amp; above), employment status (employed, not employed), marital status (married, single/divorced/widowed/separated), living alone (yes, no), perceived money insufficiency for basic living needs (yes, no), number of chronic conditions (0\u0026ndash;1, \u0026ge;\u0026thinsp;2), Patient Health Questionnaire-9 score (integer).\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n\u003ch2\u003eEmergency departments\u003c/h2\u003e\n\u003cp\u003eAfter adjusting for baseline visits and covariates, those who experienced persistent social disconnection demonstrated significantly higher odds of ED visits both in the subsequent year (OR\u0026thinsp;=\u0026thinsp;1.72, 95% CI: 1.01\u0026ndash;2.94, p\u0026thinsp;=\u0026thinsp;0.048) and at three-year follow-up (OR\u0026thinsp;=\u0026thinsp;1.77, 95% CI: 1.16\u0026ndash;2.70, p\u0026thinsp;=\u0026thinsp;0.008) compared to those who remained socially connected. Similarly, those who became socially connected also exhibited higher odds of ED visits compared to those who remained socially connected in the subsequent year (OR\u0026thinsp;=\u0026thinsp;1.94, 95% CI: 1.14\u0026ndash;3.32, p\u0026thinsp;=\u0026thinsp;0.015) and at three-year follow-up (OR\u0026thinsp;=\u0026thinsp;2.07, 95% CI: 1.37\u0026ndash;3.12, p\u0026thinsp;=\u0026thinsp;0.001). No significant differences in IRRs were observed across groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003eSpecialist outpatient clinics\u003c/h2\u003e\n\u003cp\u003eNo significant associations were observed between changes in social connectedness and subsequent SOC visits at one-year and three-year follow-ups.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003ePolyclinics\u003c/h2\u003e\n\u003cp\u003eCompared to those who remained socially connected, the group with persistent social disconnection exhibited higher rates of polyclinic visits in both the subsequent year (IRR\u0026thinsp;=\u0026thinsp;1.37, 95% CI: 1.12\u0026ndash;1.68, p\u0026thinsp;=\u0026thinsp;0.003) and at three-year follow-up (IRR\u0026thinsp;=\u0026thinsp;1.25, 95% CI: 1.02\u0026ndash;1.54, p\u0026thinsp;=\u0026thinsp;0.033), controlling for baseline visits and covariates. No significant differences in ORs were observed across groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n\u003ch2\u003eAssociation between changes in social connectedness and subsequent healthcare costs\u003c/h2\u003e\n\u003cp\u003eChanges in social connectedness were significantly associated with unadjusted costs for hospitalizations, polyclinic visits, and SOC visits, but not ED visits (Supplementary File, Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). For the three settings where significant associations were observed, the group who remained socially disconnected exhibited the highest mean cost, followed by those who became socially disconnected, then those who became socially connected, with those who remained socially connected demonstrating the lowest mean cost (Supplementary File, Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n\u003ch2\u003eIn-patient wards\u003c/h2\u003e\n\u003cp\u003eIndividuals who remained socially disconnected demonstrated higher odds of incurring hospitalization costs in the subsequent year (OR\u0026thinsp;=\u0026thinsp;2.30, 95% CI: 1.21\u0026ndash;4.40, p\u0026thinsp;=\u0026thinsp;0.012) and at three-year follow-up (OR\u0026thinsp;=\u0026thinsp;1.89, 95% CI: 1.15\u0026ndash;3.13, p\u0026thinsp;=\u0026thinsp;0.013) compared to those who remained socially connected. No significant associations with hospitalization costs were observed for the other groups (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAssociations of changes in social connection with healthcare cost at one-year and three-year follow-ups by healthcare settings (in-patient wards, emergency departments, specialist outpatient clinics and polyclinics).\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTimepoint\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eHealthcare setting\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eIsolation/loneliness status\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n\u003cp\u003eMedian (IQR)\u003c/p\u003e\n\u003cp\u003e(SGD)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAdjusted OR \u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAdjusted CR \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e(95% CI)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eZero values excluded\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSubsequent year\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eIn-patient wards\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e518\u0026thinsp;\u0026plusmn;\u0026thinsp;4,555\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1,360\u0026thinsp;\u0026plusmn;\u0026thinsp;6,389\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.66 (0.83\u0026ndash;3.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.84 (0.39\u0026ndash;1.78)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2,716\u0026thinsp;\u0026plusmn;\u0026thinsp;9,598\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.30 (1.21\u0026ndash;4.40)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.63 (0.29\u0026ndash;1.34)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e750\u0026thinsp;\u0026plusmn;\u0026thinsp;3,338\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.28 (0.56\u0026ndash;2.90)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.49 (0.20\u0026ndash;1.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e \u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEmergency departments\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e29.70\u0026thinsp;\u0026plusmn;\u0026thinsp;157\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e132\u0026thinsp;\u0026plusmn;\u0026thinsp;397\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.88 (1.10\u0026ndash;3.22)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.57 (1.10\u0026ndash;2.24)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e192\u0026thinsp;\u0026plusmn;\u0026thinsp;495\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.65 (0.96\u0026ndash;2.85)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.50 (1.03\u0026ndash;2.20)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e71.6\u0026thinsp;\u0026plusmn;\u0026thinsp;222\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.36 (0.72\u0026ndash;2.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.15 (0.77\u0026ndash;1.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd rowspan=\"4\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSpecialist outpatient clinics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e233\u0026thinsp;\u0026plusmn;\u0026thinsp;846\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e640\u0026thinsp;\u0026plusmn;\u0026thinsp;2,770\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;214)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.16 (0.71\u0026ndash;1.90)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.77 (1.08\u0026ndash;2.91)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e637\u0026thinsp;\u0026plusmn;\u0026thinsp;1,583\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;533)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.63 (1.00\u0026ndash;2.64)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.07 (0.67\u0026ndash;1.69)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e522\u0026thinsp;\u0026plusmn;\u0026thinsp;1,459\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;229)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.67 (0.98\u0026ndash;2.83)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.98 (0.58\u0026ndash;1.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePolyclinics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e181\u0026thinsp;\u0026plusmn;\u0026thinsp;450\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;115)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e258\u0026thinsp;\u0026plusmn;\u0026thinsp;611\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;172)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.03 (0.66\u0026ndash;1.60)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.89 (0.68\u0026ndash;1.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e405\u0026thinsp;\u0026plusmn;\u0026thinsp;687\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;581)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.33 (0.83\u0026ndash;2.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.13 (0.88\u0026ndash;1.44)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e313\u0026thinsp;\u0026plusmn;\u0026thinsp;850\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;223)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.93 (0.57\u0026ndash;1.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.18 (0.89\u0026ndash;1.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eThree years\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(cumulative)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eIn-patient wards\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1,036\u0026thinsp;\u0026plusmn;\u0026thinsp;5,450\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3,413\u0026thinsp;\u0026plusmn;\u0026thinsp;10,541\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.64 (0.90\u0026ndash;2.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.32 (0.78\u0026ndash;2.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6,352\u0026thinsp;\u0026plusmn;\u0026thinsp;19,399\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;2,094)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.89 (1.15\u0026ndash;3.13)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.58 (0.93\u0026ndash;2.70)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1,940\u0026thinsp;\u0026plusmn;\u0026thinsp;6,272\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.37 (0.75\u0026ndash;2.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.80 (0.43\u0026ndash;1.49)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEmergency departments\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e99.70\u0026thinsp;\u0026plusmn;\u0026thinsp;340\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e343\u0026thinsp;\u0026plusmn;\u0026thinsp;707\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;422)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.99 (1.32\u0026ndash;3.00)**\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.34 (1.03\u0026ndash;1.74)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e413\u0026thinsp;\u0026plusmn;\u0026thinsp;824\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;515)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.72 (1.13\u0026ndash;2.64)*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.14 (0.86\u0026ndash;1.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e203\u0026thinsp;\u0026plusmn;\u0026thinsp;454\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;282)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.56 (0.97\u0026ndash;2.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.99 (0.73\u0026ndash;1.34)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSpecialist outpatient clinics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e717\u0026thinsp;\u0026plusmn;\u0026thinsp;2,469\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;302)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1,486\u0026thinsp;\u0026plusmn;\u0026thinsp;4,162\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;989)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.12 (0.73\u0026ndash;1.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.51 (0.97\u0026ndash;2.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1,978\u0026thinsp;\u0026plusmn;\u0026thinsp;6,945\u003c/p\u003e\n\u003cp\u003e153 (0\u0026ndash;1,580)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.45 (0.94\u0026ndash;2.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.19 (0.77\u0026ndash;1.83)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1,986\u0026thinsp;\u0026plusmn;\u0026thinsp;8,416\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;566)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.54 (0.97\u0026ndash;2.46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.23 (0.76\u0026ndash;1.99)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePolyclinics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;670)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e554\u0026thinsp;\u0026plusmn;\u0026thinsp;1,363\u003c/p\u003e\n\u003cp\u003e0 (0\u0026ndash;437)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially connected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e784\u0026thinsp;\u0026plusmn;\u0026thinsp;1,877\u003c/p\u003e\n\u003cp\u003e49.20 (0\u0026ndash;538)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.24 (0.83\u0026ndash;1.86)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.82 (0.63\u0026ndash;1.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRemained socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1,144\u0026thinsp;\u0026plusmn;\u0026thinsp;1,953\u003c/p\u003e\n\u003cp\u003e115 (0\u0026ndash;1,535)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.07 (0.69\u0026ndash;1.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.13 (0.87\u0026ndash;1.48)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBecame socially disconnected\u003c/strong\u003e (n\u0026thinsp;=\u0026thinsp;132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e850\u0026thinsp;\u0026plusmn;\u0026thinsp;1,974\u003c/p\u003e\n\u003cp\u003e103 (0\u0026ndash;808)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.34 (0.84\u0026ndash;2.12)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.07 (0.80\u0026ndash;1.42)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003e\u003cem\u003e* p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eColumn p-values derived from Kruskal-Wallis H tests\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eOdds Ratio (OR) obtained from logistic regressions, adjusted for the following covariates: baseline cost (yes, no), age group (younger adults, older adults), gender (male, female), ethnicity (Chinese, non-Chinese), education (secondary school \u0026amp; below, post-secondary school \u0026amp; above), employment status (employed, not employed), marital status (married, single/divorced/widowed/separated), living alone (yes, no), perceived money insufficiency for basic living needs (yes, no), number of chronic conditions (0\u0026ndash;1, \u0026ge;\u0026thinsp;2), Patient Health Questionnaire-9 score (integer).\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eCost Ratio (CR) obtained from Gamma regressions, adjusted for the following covariates: baseline cost (numeric), age group (younger adults, older adults), gender (male, female), ethnicity (Chinese, non-Chinese), education (secondary school \u0026amp; below, post-secondary school \u0026amp; above), employment status (employed, not employed), marital status (married, single/divorced/widowed/separated), living alone (yes, no), perceived money insufficiency for basic living needs (yes, no), number of chronic conditions (0\u0026ndash;1, \u0026ge;\u0026thinsp;2), Patient Health Questionnaire-9 score (integer).\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n\u003ch2\u003eEmergency departments\u003c/h2\u003e\n\u003cp\u003eCompared to those who remained socially connected, individuals who remained socially disconnected exhibited higher cost ratio in the subsequent year (CR\u0026thinsp;=\u0026thinsp;1.50, 95% CI: 1.03\u0026ndash;2.20, p\u0026thinsp;=\u0026thinsp;0.039) and higher odds ratio at three-year follow-up (OR\u0026thinsp;=\u0026thinsp;1.72, 95% CI: 1.13\u0026ndash;2.64, p\u0026thinsp;=\u0026thinsp;0.012). Individuals who became socially connected demonstrated higher ED visit costs both in the subsequent year (OR\u0026thinsp;=\u0026thinsp;1.88, 95% CI: 1.10\u0026ndash;3.22, p\u0026thinsp;=\u0026thinsp;0.021; CR\u0026thinsp;=\u0026thinsp;1.57, 95% CI: 1.10\u0026ndash;2.24, p\u0026thinsp;=\u0026thinsp;0.014) and at three-year follow-up (OR\u0026thinsp;=\u0026thinsp;1.99, 95% CI: 1.32-3.00, p\u0026thinsp;=\u0026thinsp;0.001; CR\u0026thinsp;=\u0026thinsp;1.34, 95% CI: 1.03\u0026ndash;1.74, p\u0026thinsp;=\u0026thinsp;0.032).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n\u003ch2\u003eSpecialist outpatient clinics\u003c/h2\u003e\n\u003cp\u003eIn the subsequent year, individuals who remained socially disconnected had higher odds of incurring SOC visit costs (OR\u0026thinsp;=\u0026thinsp;1.63, 95% CI: 1.00-2.64, p\u0026thinsp;=\u0026thinsp;0.049) while individuals who became socially connected had higher cost ratio (CR\u0026thinsp;=\u0026thinsp;1.77, 95% CI: 1.09\u0026ndash;2.91, p\u0026thinsp;=\u0026thinsp;0.025) compared to those who remained socially connected. At three-year follow-up, no significant associations were observed between change in social connectedness and cumulative costs incurred across groups.\u003c/p\u003e\n\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\n\u003ch2\u003ePolyclinics\u003c/h2\u003e\n\u003cp\u003eNo significant associations were observed between changes in social connectedness and subsequent costs incurred for polyclinic visits across groups at either follow-up.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003eMain findings\u003c/h2\u003e \u003cp\u003eThis study examined the associations between temporal changes in social connectedness and subsequent one-year and cumulative three-year healthcare utilization as well as cost at four healthcare settings in Singapore. At both time points, persistent social disconnection was associated with increased hospitalizations, polyclinic visits, and ED visits, and higher costs for hospitalizations and ED visits, compared to those who remained socially connected. In addition, it was also associated with higher odds of incurring SOC costs at one-year follow-up. Encouragingly, protective effects were observed for subsequent hospitalizations and polyclinic visits among individuals who became socially connected, although not for ED visits and associated costs.\u003c/p\u003e \u003cp\u003eThe observations of higher healthcare utilization and costs among the group with persistent social disconnection are aligned with our hypothesis. This could be explained by various pathways through which social isolation and loneliness influence health and healthcare-seeking behaviors. For instance, social disconnection may directly increase healthcare needs through experiences of pain that are disruptive to daily activities \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e or the development of acute health conditions triggered by prolonged stress \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Socially disconnected individuals might also prefer to self-medicate \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e or delay seeking medical care due to contributing factors such as low health literacy \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e or financial constraints \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Consequently, this avoidant behavior may lead to worsening health conditions that ultimately necessitate emergency care in the longer term \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Moreover, the observed effects at three-year follow-up suggest that, while social isolation and loneliness may be transitory states, their health impacts could persist beyond the period of social disconnectedness itself.\u003c/p\u003e \u003cp\u003eContrary to our expectations, however, individuals who became socially disconnected did not exhibit higher subsequent healthcare utilization and costs compared to those who remained socially connected. We posit that this could be due to several factors. First, there may be a lag time between becoming socially disconnected and observable changes in healthcare outcomes, whereby effects may not yet be detectable within our follow-up period. Second, these individuals may have mainly engaged in healthcare avoidant behaviors. It is also plausible that the relatively small sample size of this group (11.2%) may have limited statistical power to detect associations. This warrants further investigation, integrated with qualitative approaches, to better understand the nuances of these observed patterns.\u003c/p\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eIn-patient wards\u003c/h2\u003e \u003cp\u003eThis study's findings align with previous research using administrative healthcare data which demonstrated that social disconnection was associated with increased hospital admissions \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The protective effects observed among those who became socially connected suggest that interventions aimed at improving social connectedness may help reduce hospitalizations, the most resource-intensive form of care. However, the elevated odds at three-year follow-up raise the possibility that sustained social connectedness may be critical in maintaining these protective effects over time. Potential mechanisms underlying these protective effects include reduced stress-induced adverse health outcomes \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, improved medication adherence \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, and engagement in healthier lifestyle choices \u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eEmergency departments\u003c/h2\u003e \u003cp\u003eParadoxically, individuals who became socially connected demonstrated higher ED visits and costs at both follow-ups compared to those who remained socially connected, with odds that were even higher than those observed among the group with persistent social disconnection. There are several potential explanations for this counterintuitive observation. It remains unclear whether individuals with apparent improvements subsequently reverted to their socially disconnected status, or whether prior exposure had already impacted their health \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. It is also possible that these individuals may have experienced extended periods of social disconnection preceding and between data collections, or encountered frequent relapses due to vulnerability from socioeconomic factors \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. Moreover, as improved social connections may facilitate health-seeking behavior \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, this could explain why this group exhibited higher urgent care needs than those who remained socially connected, with utilization patterns resembling the persistently socially disconnected group. Last but not least, our analyses only adjusted for the number of chronic conditions, while disease severity could have been a stronger mediator of healthcare utilization and costs. These patterns suggest that the healthcare impacts of social disconnectedness may persist even after social circumstances improve, highlighting the importance of early intervention and prevention strategies.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eSpecialist outpatient clinics\u003c/h2\u003e \u003cp\u003eThis study addresses an understudied area in the literature regarding the association of social disconnectedness with outpatient specialist consultations. While SOC visit frequency did not differ by groups after adjusting for baseline visits and covariates such as multimorbidity, persistently socially disconnected individuals displayed higher odds of incurring SOC costs at one-year follow-up. Among those who incurred SOC costs, individuals who became socially connected demonstrated higher cost ratios at one-year but not three-year follow-up. The lack of significant associations with visit frequency, despite differences in costs, suggests that these two groups might have presented with more complex care needs requiring costlier specialist care in the shorter term.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003ePolyclinics\u003c/h2\u003e \u003cp\u003eCompared to those who remained socially connected, the group with persistent social disconnection exhibited higher rates of polyclinic visits at both one-year and three-year follow-ups after controlling for baseline visits and covariates. As polyclinics cater to a sizeable patient population with chronic conditions by providing a comprehensive range of services at subsidized rates in Singapore \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, the sustained higher utilization among persistently disconnected polyclinic attendees may reflect ongoing management of chronic health conditions that could have been exacerbated by social disconnectedness. Encouragingly, individuals who became socially connected did not demonstrate higher polyclinic utilization, compared to those who remained socially connected at either follow-up, suggesting protective effects similar to that observed for hospitalizations. This finding that strengthening social ties may help reduce the burden on primary care services is particularly noteworthy for Singapore's healthcare system, where polyclinics are already experiencing significant resource constraints from high patient volumes \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStrengths and Limitations\u003c/h3\u003e\n\u003cp\u003eTo the best of our knowledge, this is the first study in Singapore to examine social isolation, loneliness, and their effects on subsequent healthcare utilization and cost using administrative data from multiple care settings, providing insights specific to Singapore's unique sociocultural context. The advantages of utilizing administrative data include mitigating potential recall bias and enhancing the detection of effects \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Furthermore, the prospective analysis approach minimizes possible reverse causality, whereby healthcare utilization might have contributed to changes in social connectedness.\u003c/p\u003e \u003cp\u003eHowever, this study combined social isolation and loneliness into the broader concept of social disconnection, which carries the assumption that both constructs have equivalent impacts on healthcare utilization and cost outcomes. Although ideally these constructs would be examined separately, differentiating their individual effects was not within the scope of this study due to the small sample sizes of the groups with changes in social connectedness, which were reduced further when investigating utilization by healthcare setting. Additionally, while holding covariates constant at baseline values enhanced interpretability of results, potential changes in time-varying sociodemographic factors that may influence social isolation and loneliness status were not accounted for. We also could not account for potential fluctuations in social connectedness between measurement points, and the lag time between changes in social connectedness and health outcomes may mean that some effects might not be detectable within our follow-up period. Finally, this study was limited to participants with healthcare utilization and cost records at NHG Health institutions. This exclusion of individuals who did not utilize NHG Health\u0026rsquo;s services may introduce selection bias, affect generalizability, and underestimate the total healthcare utilization and costs for those who sought care from other healthcare providers.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eImplications and future directions\u003c/h2\u003e \u003cp\u003eAs Singapore works to meet rising healthcare demands from a rapidly aging population seeks to keep costs contained \u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, our results suggest that interventions targeting social connectedness could yield cost savings and ease resource strain across multiple healthcare settings.\u003c/p\u003e \u003cp\u003eThe protective effects observed for those who became socially connected suggest that social prescribing initiatives and community-based interventions could be cost-effective strategies for reducing healthcare burden. Among those who remained socially disconnected, there was a higher proportion of older adults (62.0%), underscoring the vulnerability of this demographic. In Singapore, there has been an active push to promote social engagement and community integration among the older adult population. For instance, the national Age Well SG program, launched in 2023, has various community initiatives to engage, encourage and enable seniors to keep physically and socially active \u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Such community programs that promote social connections through group activities or volunteer opportunities can help to reduce feelings of loneliness and improve health outcomes \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Additionally, there are continual outreach efforts to older adults who may be socially isolated by the Silver Generation Office, the senior engagement arm of the Agency for Integrated Care that was established by the Ministry of Health Singapore \u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn light of these efforts, future studies could not only evaluate the effectiveness of existing initiatives in addressing social isolation and loneliness, but also assess the individual and collective impacts on healthcare utilization and associated costs using population-representative administrative data. Building upon our findings of consistent associations between social disconnectedness and subsequent hospitalizations in Singapore's context, future research may also examine more granular utilization outcomes such as the length of stay and types of hospitalizations. For instance, Christiansen et al. (2023) observed that loneliness was linked to longer hospital stays in the Danish general population \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and Molloy et al. (2010) noted that loneliness was associated with unplanned hospitalizations but not planned admissions among community-dwelling adults in Ireland \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Where sample sizes permit, studies could investigate the associations of social isolation and loneliness with healthcare utilization separately to ascertain whether there are differential patterns of effects \u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. Evidence from these studies would provide valuable insights to inform the refinement of targeted interventions as well as healthcare policy decisions.\u003c/p\u003e \u003cp\u003eFinally, these findings underscore the importance of addressing social connectedness as a modifiable determinant of healthcare utilization. Policymakers may consider integrating social connectedness screening and interventions into Singapore's broader health strategies, such as Healthier SG, which emphasizes preventive care and population health management. Given that screening tools for social isolation and loneliness require minimal cost and time to implement, healthcare stakeholders may consider the systematic implementation of such screening tools to identify high-risk individuals, as well as enhanced integration of social support services and therapeutic interventions within healthcare delivery systems. These strategies would facilitate timely intervention and potentially reduce the burden on healthcare utilization and associated costs, particularly hospitalizations. For instance, individuals may require referral to structured interventions such as cognitive-behavioral therapy to alleviate feelings of loneliness if community activities are less effective for their needs \u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. However, it should be noted that these strategies might shift healthcare utilization patterns rather than decrease them overall. For example, if primary care professionals were to be the first line of screening and intervention for social isolation and loneliness, utilization may increase in this setting \u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. Insights from qualitative studies could therefore illuminate the acceptability and feasibility of addressing social disconnectedness in clinical and community settings within Singapore's context, as older people may view loneliness as a personal problem and demonstrate resistance towards addressing it in primary care settings \u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePersistent social disconnection was associated with higher healthcare utilization and costs across multiple healthcare settings compared to those who remained socially connected. While becoming socially connected demonstrated protective effects for subsequent hospitalizations and polyclinic visits, this group consistently demonstrated higher ED visits and costs at both one-year and three-year follow-ups, which warrants further research to elucidate the underlying mechanisms, including whether improved social connections facilitate earlier urgent care-seeking behavior or reflect persistent health vulnerabilities from prior social disconnection. No significant associations with healthcare utilization and costs were observed for those who became socially disconnected across all care settings. These findings suggest that proactive approaches to maintain or improve social connections, particularly among older adults who comprised the majority of those persistently socially disconnected, may help ease healthcare resource strains and yield cost savings by reducing hospitalizations, which are costly to healthcare and economic systems.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics declaration\u003c/h2\u003e \u003cp\u003e The PHI study was approved by the ethics review committee of the National Healthcare Group Domain Specific Review Board (Reference Number: 2015/00269). Written informed consent was obtained from all individual participants after they were being informed about the study objectives and the safeguards put in place so that confidentiality of the collected data is maintained.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work did not receive any external funding support. All authors were employees of the National Healthcare Group Pte Ltd. However, the employer had no role in / influence on study design, data collection and analysis, result interpretation, decision to publish, or preparation of the manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eG.H. analyzed and interpreted the data, drafted the initial manuscript, and made subsequent revisions. C.W.Y. interpreted the data and reviewed the article. L.G. conceptualized the study, interpreted the data, and reviewed and revised the article. All authors read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNewall, N. E. G. \u0026amp; Menec, V. H. Loneliness and social isolation of older adults: Why it is important to examine these social aspects together. \u003cem\u003eJ. 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Care Commun.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e, 1733\u0026ndash;1742. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1111/hsc.12438\u003c/span\u003e\u003cspan address=\"10.1111/hsc.12438\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Social isolation, loneliness, healthcare utilization, healthcare cost, longitudinal study","lastPublishedDoi":"10.21203/rs.3.rs-8402329/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8402329/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSocial isolation and loneliness are linked with adverse health outcomes, potentially increasing healthcare demands, yet their impacts on healthcare utilization in Singapore remain underexplored. This longitudinal study examined how temporal changes in social connectedness impact subsequent healthcare utilization and costs.\u003c/p\u003e \u003cp\u003eData from a population health survey were linked with an administrative healthcare database, and participants without any records were excluded. Social isolation and loneliness were assessed with the Lubben Social Network Scale-6 and three-item UCLA Loneliness Scale, respectively. Baseline characteristics were compared using Chi-square or Kruskal-Wallis H tests. Two-step hurdle models investigated the associations between status change and subsequent healthcare utilization and costs, adjusting for baseline values and covariates.\u003c/p\u003e \u003cp\u003eAmong 1,182 participants (55% female; 61.3% aged\u0026thinsp;\u0026lt;\u0026thinsp;60), 11.2% became socially disconnected and 15.2% became socially connected. Persistent social disconnection (16.9%) was associated with increased hospitalizations, polyclinic visits, and ED visits, and higher hospitalizations and ED costs, at both one-year and three-year follow-ups, compared to those who remained socially connected (56.7%). Becoming socially connected showed protective effects for subsequent hospitalizations and polyclinic visits, but not for ED visits and associated costs.\u003c/p\u003e \u003cp\u003eAmong healthcare users, alleviating social isolation and loneliness could help reduce costly hospitalizations and ease resource strains on polyclinic services.\u003c/p\u003e","manuscriptTitle":"Examining associations of changes in social connectedness with healthcare utilization and costs: A prospective study among Singapore adults","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 06:26:46","doi":"10.21203/rs.3.rs-8402329/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-27T08:42:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T01:44:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T02:12:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-19T04:54:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173330527008872175527775684355313086240","date":"2026-02-19T02:20:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-18T15:18:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"133136212203757797406982569039986606248","date":"2026-02-16T02:15:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238206702873156851687801055272226576429","date":"2026-02-16T00:31:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"287316878511234366629463964327329909171","date":"2026-02-15T16:27:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-24T06:07:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"330177580082641841578318863240162985996","date":"2026-01-09T07:44:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-09T07:14:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-27T10:32:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-23T22:46:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-22T03:41:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-12-22T03:34:47+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":"af372737-6cbc-4843-8b4e-d1dff5294a3e","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":60955230,"name":"Health sciences/Health care"},{"id":60955231,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-04-29T14:23:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 06:26:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8402329","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8402329","identity":"rs-8402329","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}