Association between hypertension and social isolation based on the ELSA database

Association between hypertension and social isolation based on the ELSA database | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association between hypertension and social isolation based on the ELSA database Zhengde Lu, Xinyue Tang, Ying Shi, Guangma Xu, Yaoshi Hu, Qingwei Ji, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7896304/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Hypertension (HTN) is a common cardiovascular disease (CVD) and a major contributor to disease burden and premature mortality worldwide. Social isolation (SI), as a significant social issue affecting health, is closely associated with the onset and progression of various diseases. However, there are relatively few studies that use HTN as an outcome variable. This study aims to clarify the association between SI and the onset and progression of HTN in middle-aged and older Methods This study is based on the 10th wave of the English Longitudinal Study of Ageing (ELSA) multi-wave longitudinal data. It employs chi-square (χ2) tests, multivariate logistic regression, univariate logistic regression, ROC curves, and other multidimensional analyses to explore the association between SI and HTN in middle-aged and older adults aged 50 and above. Results The study found a significant association between SI and increased risk of HTN, making it a risk factor for HTN. In addition, stratified analysis found that SI was significantly associated with HTN in individuals aged 50 to 65 years, whereas this association was not significant in those aged > 65 years. Regardless of sex (male or female) or marital status (married or single), SI showed a significant correlation with HTN. When considering race, the significant association between SI and HTN was exclusively observed among whites. Additionally, SI was significantly linked to HTN in individuals with hardly any or no physical activity. Conclusion SI is an important risk factor for HTN, and its underlying causes are complex and diverse. Therefore, effective measures should be taken immediately to reduce SI. English Longitudinal Study of Ageing Social Isolation Hypertension Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Hypertension (HTN) is a clinical condition characterized by elevated systemic arterial blood pressure and is a major risk factor for damage to vital organs such as the heart, brain, and kidneys[ 1 – 3 ]. The 2023 WHO Global Report on Hypertension has highlighted concerning prevalence rates, estimating that by 2019, 1.3 billion adults worldwide were affected by HTN. Alarmingly, only 54% of cases were diagnosed, 42% received treatment, and a mere 21% achieved adequate blood pressure control[ 4 ]. As a major risk factor for cardiovascular diseases, HTN is a leading contributor to global morbidity and mortality. While effective treatment can reduce these risks, the current low rate of HTN control poses a significant challenge to achieving even lower blood pressure treatment targets. Thus, Therefore, urgent large-scale studies are imperative to systematically identify and assess HTN risk factors, facilitating the development of improved early intervention and precision treatment strategies. The concept of social isolation (SI) was initially introduced in 1979 to describe an objective condition marked by reduced social networks and absence of social ties. It occurs when an individual's social connections diminish notably in quantity and quality, leading to a significant decrease in social network size, interaction frequency, and relationship depth[ 5 , 6 ]. Survey data reveal that SI is a significant concern, affecting up to 25–33% of older adults globally. With aging populations, rapid urbanization, and evolving social structures, the population vulnerable to SI is expanding[ 7 , 8 ]. SI is a key risk factor for various neuropsychiatric conditions such as anxiety, depression, and cognitive decline, and is a strong predictor of physical health decline[ 9 – 11 ]. A prospective observational study demonstrated a direct link between SI and a 29% higher risk of mortality, a 29% increased risk of coronary heart disease, and a 32% elevated risk of stroke. Furthermore, a consistent association between SI and mortality risk is evident across countries with diverse levels of economic development[ 12 ]. While research on the relationship between SI and HTN remains limited in scope, existing studies have identified a robust link between the two. For example, a study conducted in the United States demonstrated that SI significantly raises the likelihood of developing HTN in young and early middle-aged adults, especially in men who are socially isolated from their family and friends[ 13 , 14 ]. These results suggest that social isolation—a key psychosocial factor—likely contributes significantly to the development of HTN. Additional research is needed to clarify the association between social isolation (SI) and HTN, offering new insights and approaches for preventing and managing HTN, with a focus on psychosocial support and lifestyle adjustments. The English Longitudinal Study of Ageing (ELSA) is a large-scale prospective cohort study focused on individuals aged 50 and above in England, overseen by institutions such as University College London[ 15 ]. Since its inception in 2002, data have been gathered by the research team biennially via comprehensive face-to-face interviews, self-administered questionnaires, physical assessments, and biomarker evaluations. The study encompasses vital domains including health status, physical capabilities, cognitive and mental well-being, social involvement, familial background, financial assets, and retirement arrangements[ 16 ]. Numerous investigations have leveraged the ELSA dataset. For example, one inquiry revealed a notable increase in the risk of depression among older adults, particularly in low- and middle-income nations, due to digital exclusion[ 17 ]. Another study reported no discernible link between initial dietary patterns and the development or advancement of coronary artery calcification.[ 18 ] In essence, ELSA serves as a robust data repository for scrutinizing the enduring interplay of health and psychosocial elements in middle-aged and elderly cohorts, enabling thorough exploration of pivotal topics in gerontological research. This research examines the link between social isolation (SI) and hypertension (HTN) onset in individuals aged 50 and above in England, using longitudinal data from Wave 10 (2020–2021) of the ELSA. The study seeks to offer empirical support for implementing social and behavioral interventions in the prevention and management of hypertension. 2. Materials and methods 2.1 Data origin The data is derived from the English Longitudinal Study of Ageing (ELSA) database ( https://www.elsa-project.ac.uk ), which targets individuals aged 50 or over and their partners, living in private households in England. Employing a stratified random sampling design, this study recruited a nationally representative sample of middle-aged and older participants, aiming to gain in-depth insights into the health, social, psychological, and economic aspects of population aging. The database contains detailed data collected from participants at regular intervals (approximately every two years), including in-person interviews, self-administered questionnaires, physical measurements, and biomarker tests. This study used wave 10 (2020–2021) as the research baseline. The process of data acquisition and use strictly adhered to the approval requirements of the National Health Service (NHS) Research Ethics Committee in the UK, and all participants signed written informed consent forms. 2.2 Ascertainment of variables The covariates include age (classified as > 65 years, ≤ 65 years) [DHAGE], sex (male and female) [DHSEX], ethnics (white/non-white) [FQETHNMR], marriage (married/single) [DIMARR], health (excellent/good/fair/bad/very bad) [HEHELF], activity frequency (hardly ever, or never/more than once a week/once a week/one to three times a month) [HEACTA], vision problems (blind/non-blind) [HEEYE], hearing problems (poor/non-poor) [HEHEAR], diabetes (with/without) [HEHaveDI], memory-related diseases (with/without) [HEHaveAD], and stroke (with/without) [HEEverST]. The outcome is hypertension (HTN) (with/without) [HEHaveBP], and the exposure factor is social isolation (SI) (yes or no) [PSCEDE] ( Table 1 ) . In the ELSA database, the diagnostic criteria for the aforementioned variables (diabetes, memory-related diseases, stroke, and hypertension) are primarily based on self-reported physician diagnosis or self-reported information during follow-up assessments. Specifically, participants were asked the core question: "Has a doctor ever told you that you have been diagnosed with diabetes, a memory-related disease, stroke, or hypertension?". SI is defined such that participants score 1 point for each of the following criteria: being unmarried (including separated, divorced, widowed, or never married), having infrequent contact with their children (via telephone, in person, or email) on a weekly basis, and not participating in any social activities (including interacting with friends, playing chess or cards, and attending sports, social, or other clubs) in the past month. The social isolation index ranges from 0 to 3, with higher scores indicating a greater degree of social isolation. Participants with a score of ≥ 1 were categorized into the socially isolated group[ 19 ] . Table 1 Variable and its number information table Variable level variable definition Data set and definition number year Age ≤ 65 covariates DHAGE 2020–2021 > 65 Sex Female covariates DHSEX 2020–2021 Male Race Non-White covariates FQETHNMR 2020–2021 White Marriage Married covariates DIMARR 2020–2021 Single Health Excellent covariates HEHELF 2020–2021 Good Fair Bad Very bad Activities Hardly ever, or never covariates HEACTA 2020–2021 More than once a week Once a week One to three times a month Vision_problems Non-blind covariates HEEYE 2020–2021 Blind Hearing_problems Non-poor covariates HEHEAR 2020–2021 Poor Diabetes Without covariates HEHaveDI 2020–2021 With Memory_related_disease Without covariates HEHaveAD 2020–2021 With Continued Table 1 Variable and its number information table Stroke Without covariates HEEverST 2020–2021 With HTN Without outcome HEHaveBP 2020–2021 With SI Yes exposure factor PSCEDE 2020–2021 2.3 Exclusion criteria The exclusion criteria for this study were [ 20 , 21 ]participants with missing social isolation variables; participants whose covariates are marked as missing or rejected; participants who did not meet HTN or lack of information; participants with baseline age < 50 years (ELSA lower limit of enrollment). 2.4 Statistical analysis All visualizations of charts in this research were performed using R software (v.5.2.3)[ 22 ]. The baseline analysis expressed categorical variables as percentages, used Pearson's chi-squared (χ 2 ) tests to analyze differences between participants and various baseline characteristics, and the R package "tableone" (v 0.13.2) [ 23 ] was used to draw the baseline table to complete the collation and presentation of relevant data. The statistical power for the difference in proportions between the two independent samples was calculated using the pwr package (v 1.3.0) [ 24 ].The multinomial logistic regression model was used to construct the model, and the results are presented as adjusted odds ratios (ORs) and 95% confidence intervals (CIs) (p value < 0.05). Three models were constructed: model 1 did not adjust for any variables; model 2 adjusted for age, sex, and race (minimal adjustment model); model 3 further adjusted for marriage, health, activity frequency, vision problems, hearing problems, diabetes, memory-related diseases, and stroke (fully adjusted model). Additionally, the multinomial logistic regression model was used to analyze the association between SI and HTN in the three models and various variables. Univariate logistic regression analysis was used to analyze the association between SI and HTN in subgroups of sex, race, marital status, and activity frequency. The results were presented using the R packages "tableone" (v 0.13.2) and "forestplot" (v 3.1.1)[ 25 ]. Based on Model 3, the receiver operating characteristic (ROC > 0.7) curve was plotted using the R package “pROC” (v 1.18.0) [ 26 ] to analyze the predictive efficacy of SI on HTN risk and the predictive efficacy of HTN risk after model adjustment. The statistical significance level was set at p < 0.05. 3 Results 3.1 Baseline Characteristics of Participants This study utilized data from the tenth wave (2020–2021) of the ELSA database to summarize various variables for participants diagnosed with HTN, with 7589 participants. Based on the exclusion criteria, participants with missing variables related to social isolation were first excluded, leaving 7,100 participants (retention rate: 93.6%); participants with missing or refused covariates were then excluded, leaving 4,519 participants (retention rate: 59.5%); participants who did not meet the criteria for HTN or lacked relevant information were excluded, leaving 4,508 participants (retention rate: 59.4%); Finally, participants with a baseline age younger than 50 years were excluded, resulting in a final sample of 4,413 participants included in the analysis (retention rate: 58.1%). Participants were divided into a hypertension group (disease group) and a non-hypertension group (normal group) based on their hypertension status, with 1,607 participants in the disease group (157 reported loneliness, representing 9.77%) and 2,824 participants in the normal group (193 reported loneliness, accounting for 6.83%) ( Fig. 1 ). The statistical power for the difference in proportions between the two independent samples was calculated. The results showed an effect size of Cohen’s h = 0.107, with a significance level of α = 0.05, corresponding to a statistical power of 92.8%, indicating that the sample size was sufficient to detect differences in proportions between the two groups. Further, a proportion test was conducted to examine the difference in loneliness proportions between the two groups. The results revealed a statistically significant difference (χ² = 11.731, df = 1, p = 0.000615), with a 95% CI of (-0.0471, -0.0116). These findings suggest that the proportion of loneliness in the hypertension group was significantly higher than that in the normal group. The baseline characteristics of participants indicated that HTN was not associated with memory-related diseases, but was significantly associated with SI and other covariates. ( Table 2 ) . Table 2 Participants ' baseline characteristics level control disease p n 2824 1607 SI(%) No 2631 (93.2) 1450 (90.2) 0.001 Yes 193 ( 6.8) 157 ( 9.8) Age (%) ≤ 65 1464 (51.8) 508 (31.6) 65 1360 (48.2) 1099 (68.4) Sex (%) Female 1580 (55.9) 716 (44.6) < 0.001 Male 1244 (44.1) 891 (55.4) Race (%) Non-White 166 ( 5.9) 129 ( 8.0) 0.007 White 2658 (94.1) 1478 (92.0) Marriage (%) Married 2381 (84.3) 1401 (87.2) 0.011 Single 443 (15.7) 206 (12.8) Health (%) Excellent 477 (16.9) 69 ( 4.3) < 0.001 Good 1029 (36.4) 368 (22.9) Fair 828 (29.3) 603 (37.5) Bad 371 (13.1) 388 (24.1) Very bad 119 ( 4.2) 179 (11.1) Activities (%) Hardly ever, or never 1471 (52.1) 1078 (67.1) < 0.001 More than once a week 823 (29.1) 281 (17.5) Once a week 296 (10.5) 138 ( 8.6) One to three times a month 234 ( 8.3) 110 ( 6.8) Vision_problems (%) non-blind 2782 (98.5) 1559 (97.0) 0.001 blind 42 ( 1.5) 48 ( 3.0) Hearing_problems (%) non-poor 2734 (96.8) 1521 (94.6) 0.001 poor 90 ( 3.2) 86 ( 5.4) Diabetes (%) without 2655 (94.0) 1303 (81.1) < 0.001 with 169 ( 6.0) 304 (18.9) Continued Table 2 Baseline Characteristics of Participants level control disease p Memory_related_disease (%) without 2810 (99.5) 1592 (99.1) 0.123 with 14 ( 0.5) 15 ( 0.9) Stroke (%) without 2760 (97.7) 1492 (92.8) < 0.001 with 64 ( 2.3) 115 ( 7.2) Values are expressed as number (percentage) . 3.2 Association analysis between SI and HTN risk The association analysis between SI and HTN showed that SI was significantly associated with HTN in the three models ( OR > 1, p value < 0.05 ) ( Table 3 ) . Among various variables, SI was also significantly associated with HTN ( p value < 0.05, OR = 1.287, 95% CI: 1.087–1.524 ), which was a risk factor for increased prevalence of HTN. In addition, we also found that age, sex, race, and health status were significantly associated with the occurrence of HTN ( p < 0.05 ). These findings suggest that in the prevention and management of HTN, we should not only pay attention to the association between SI and HTN, but also integrate other related factors to effectively develop targeted interventions. ( Fig. 2 ). Table 3 Risk association analysis between social isolation and hypertension model OR 95% CI P value SI model 1 1.346 1.142–1.587 0.0004076 model 2 1.43 1.212–1.689 0.00002372 model 3 1.287 1.087–1.524 0.003486 SI, social isolation 3.3 stratified analysis Subgroup analyses stratified by age, sex, race, marital status, and activity frequency revealed that SI was significantly associated with HTN in individuals aged 50 to 65 years, whereas this association was not significant in those aged > 65 years. Regardless of sex (male or female) or marital status (married or single), SI showed a significant correlation with HTN. When considering race, the significant association between SI and HTN was exclusively observed among whites. Additionally, SI was significantly linked to HTN in individuals with hardly any or never physical activity ( Fig. 3 ) . The above results reveal the heterogeneity of the association between SI and HTN, suggesting that the role of SI in different populations may be regulated by factors such as age, race, and activity frequency, which provides a theoretical basis for future intervention strategies for specific populations. 3.4 ROC analysis The AUC of the ROC curve results was 0.712, which was greater than 0.7, indicating that SI had a good predictive ability for HTN, and the research results had a certain reference value ( Fig. 4 ) . Discusion HTN, a prevalent chronic condition globally known as the "silent killer" for its asymptomatic nature, poses a significant risk for severe cardiovascular complications, including acute coronary syndrome, aortic dissection, stroke, and renal failure [ 27 ]. Social isolation (SI) as a psychosocial factor may detrimentally affect blood pressure regulation through stress response activation, lifestyle behavior influence, and exacerbation of psychological distress, thereby closely intertwining with hypertension onset and progression[ 28 ]. This investigation leveraged Wave 10 (202–2021) data from the ELSA database, employing chi-square (χ²) tests, univariate and multivariate logistic regression analyses, as well as ROC curve analysis to explore the SI-hypertension relationship. The findings revealed a noteworthy association between SI and increased risk, establishing SI as a significant hypertension risk factor. The study establishes a significant correlation between social isolation (SI) and an elevated risk of hypertension (HTN), identifying SI as a risk factor for HTN, consistent with prior research. Notably, a study in the United States found that SI in young to middle-aged individuals substantially increased the likelihood of developing HTN. Another U.S. study investigated gender disparities in the link between SI and HTN among older adults, revealing that isolated men faced a higher risk of HTN compared to women, in whom no such association was observed [ 13 , 14 ]. The coherence of our results implies that the relationship between SI and HTN is not incidental but likely grounded in multiple underlying mechanisms. The consistency of our results with prior research suggests this relationship is not coincidental but rooted in biological and psychological mechanisms. For instance, animal studies provide compelling evidence that chronic social isolation can initiate or exacerbate chronic stress responses [ 29 – 32 ], which subsequently activate the hypothalamic-pituitary-adrenal (HPA) axis and prompt the release of stress-related hormones such as glucocorticoids (predominantly cortisol) and angiotensin II[ 32 – 34 ]. Furthermore, animal experiments demonstrate that SI amplifies inflammatory responses and increases the release of pro-inflammatory cytokines. These cytokines damage vascular endothelial cells, impeding vasodilation; they also stimulate vascular smoot muscle cell proliferation, thickening vessel walls, narrowing lumens, increasing vascular resistance, and ultimately elevating blood pressure [ 35 ]. Beyond biological pathways, SI often triggers negative emotions such as anxiety, depression, and loneliness, closely associated with HTN risk. Studies among Native American populations in the U.S. revealed that individuals with depressive symptoms had a 54% higher risk of developing HTN during follow-up compared to those without such symptoms. Similarly, depressive symptoms have been identified as a risk factor for HTN in young Hispanic/Latino adults. Additionally, a meta-analysis showed that anxiety is linked to an increased HTN risk[ 36 – 39 ]. These findings suggest that negative emotions induced by SI, such as depression and anxiety, may act as crucial mediators, persistently activating the body's stress response system, disrupting neuroendocrine regulation, ultimately contributing to elevated blood pressure, and serving as potential HTN risk factors. To investigate population-specific links between SI and HTN, this study conducted stratified analyses based on age, sex, race, marital status, and activity frequency. The results indicated varying strengths of association across different subgroups (Fig. 3 ), offering new insights into the contextual influences of SI on HTN and informing targeted preventive measures.The age-stratified analysis revealed a significant association between SI and HTN in the 50–65 age group, whereas no significant correlation was observed in individuals aged > 65 years. These results are consistent with prior U.S. studies focusing on younger to middle-aged cohorts, potentially linked to pivotal life transitions experienced by individuals in the middle age range. Social isolation in this demographic could induce psychological stress, activating the hypothalamic-pituitary-adrenal (HPA) axis and triggering the release of stress-related hormones, thereby increasing blood pressure[ 40 ]. Conversely, older adults may demonstrate heightened adaptability or the association between SI and HTN may be masked by concurrent health conditions. This finding implies that interventions addressing social isolation in the 50–65 age group may be crucial for HTN prevention and management. SI is a recognized risk factor for HTN that can be effectively addressed through multidimensional interventions aimed at mitigating its impact on blood pressure. Among high-risk populations, such as individuals aged 50–65 years or those with little physical activity (consistent with our stratified findings), enhancing the frequency of virtual or in-person interactions-which are facilitated through video calls, social applications, or regular neighborly visits, can alleviate feelings of loneliness. Furthermore, promoting engagement in community group activities, such as social services or interest groups, has been associated with a reduction in inflammatory markers like IL-6[ 41 – 43 ], directly counteracting the pro-inflammatory pathways linked to HTN in our mechanistic discussion. Studies have shown that physical exercise not only directly reduces blood pressure but also combats loneliness by fostering social interactions—a key intervention for individuals with low activity levels, as their SI-HTN association was most pronounced. Moreover, dietary modifications, including decreasing sodium intake and increasing the consumption of fruits, vegetables, and low-fat dairy products, are more sustainable when individuals have robust social support networks, indirectly lowering the risk of HTN[ 44 – 46 ]. In conclusion, future research should delve into tailored interventions for specific populations, such as 50-65-year-olds and sedentary individuals (given their stronger SI-HTN association). Enhancing collaboration between communities and families, leveraging technological advancements, and refining policies will be practical strategies to enhance the well-being and health outcomes of vulnerable groups. This study emphasizes a notable correlation between SI and a heightened likelihood of HTN, establishing SI as a predisposing factor for HTN. The findings offer insights into potential approaches for alleviating the disease burden and exploring causal factors, emphasizing the importance of comprehensive interventions to diminish SI in forthcoming endeavors. Nevertheless, the study is subject to certain limitations that warrant attention. Given that the data were derived from a publicly available database and exclusively focused on individuals aged 50 and older in England, the sample size is relatively restricted. Subsequent investigations could address this limitation by enlarging the sample size, including more diverse racial groups, and encompassing a wider age spectrum to bolster the generalizability of the findings. Declarations Ethics approval statement ： Ethical approval was not required for this study as it exclusively utilized publicly available data and/or previously published literature. No new data involving human or animal participants were collected for this analysis. Patient consent statement： Patient consent was not required for this study as it exclusively utilized publicly available data,No new data involving human or animal participants were collected for this analysis. Availability of data and materials ： The datasets generated and/or analysed during the currentstudy are available in ELSA data,which are publicly available at[https://www.elsa-project.ac.uk] Competing interests： The authors declare that they have no competing interests. Funding statement ： Funding for this project was provided by the Ministry of Finance of China and National Health and Family Planning Commission, the Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention (22-035-18), Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases (AD17129014) and Guangxi Medical High-level Backbone Talents "139" Program (G201901006). Authors' contributions : ZLand XTconceived and designed the study. YS and GX collected the data. YH and QJ performed the statistical analysis. ZL and ZZ drafted the manuscript. All authors critically reviewed, edited, and approved the final manuscript. Acknowledgements : Not applicable. Clinical trial number: not applicable. References Pilic, L., C.R. Pedlar, and Y. Mavrommatis, Salt-sensitive hypertension: mechanisms and effects of dietary and other lifestyle factors. Nutr Rev, 2016. 74 (10): p. 645-58.DOI: 10.1093/nutrit/nuw028 Goorani, S., S. Zangene, and J.D. 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Malloy, et al., Depression and Incident Hypertension: The Strong Heart Family Study. Prev Chronic Dis, 2025. 22 : p. E06.DOI: 10.5888/pcd22.240230 Rosas, C.E., A. Pirzada, R. Durazo-Arvizu, et al., Prospective association between depressive symptoms and incident hypertension: Results from the Hispanic community health study/study of Latinos. J Affect Disord, 2025. 379 : p. 559-566.DOI: 10.1016/j.jad.2025.03.034 Pan, Y., W. Cai, Q. Cheng, et al., Association between anxiety and hypertension: a systematic review and meta-analysis of epidemiological studies. Neuropsychiatr Dis Treat, 2015. 11 : p. 1121-30.DOI: 10.2147/ndt.S77710 Hawkley, L.C., C.M. Masi, J.D. Berry, et al., Loneliness is a unique predictor of age-related differences in systolic blood pressure. Psychol Aging, 2006. 21 (1): p. 152-64.DOI: 10.1037/0882-7974.21.1.152 Zhang, H., M. Välimäki, X. Li, et al., Barriers and facilitators of digital interventions use to reduce loneliness among older adults: a protocol for a qualitative systematic review. BMJ Open, 2022. 12 (12): p. e067858.DOI: 10.1136/bmjopen-2022-067858 Katz, M.E., R. Mszar, A.A. Grimshaw, et al., Digital Health Interventions for Hypertension Management in US Populations Experiencing Health Disparities: A Systematic Review and Meta-Analysis. JAMA Netw Open, 2024. 7 (2): p. e2356070.DOI: 10.1001/jamanetworkopen.2023.56070 Elliot, A.J., K.L. Heffner, C.J. Mooney, et al., Social Relationships and Inflammatory Markers in the MIDUS Cohort: The Role of Age and Gender Differences. J Aging Health, 2018. 30 (6): p. 904-923.DOI: 10.1177/0898264317698551 Kim, D. and J.W. Ha, Hypertensive response to exercise: mechanisms and clinical implication. Clin Hypertens, 2016. 22 : p. 17.DOI: 10.1186/s40885-016-0052-y Lim, G.B., Hypertension: Low sodium and DASH diet to lower blood pressure. Nat Rev Cardiol, 2018. 15 (2): p. 68.DOI: 10.1038/nrcardio.2017.214 Wilson, D.K. and G. Ampey-Thornhill, The role of gender and family support on dietary compliance in an African American adolescent hypertension prevention study. Ann Behav Med, 2001. 23 (1): p. 59-67.DOI: 10.1207/s15324796abm2301_9 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 13 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers invited by journal 27 Nov, 2025 Editor invited by journal 02 Nov, 2025 Editor assigned by journal 27 Oct, 2025 Submission checks completed at journal 27 Oct, 2025 First submitted to journal 19 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7896304","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":551957092,"identity":"43d73cfc-120a-4f9b-b6d3-30b4c479aa8b","order_by":0,"name":"Zhengde Lu","email":"","orcid":"","institution":"First Affiliated Hospital of GuangXi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhengde","middleName":"","lastName":"Lu","suffix":""},{"id":551957094,"identity":"67fa1dd6-6826-4adf-ae79-8a40064e406b","order_by":1,"name":"Xinyue Tang","email":"","orcid":"","institution":"The People's Hospital of Guangxi Zhuang 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1","display":"","copyAsset":false,"role":"figure","size":374375,"visible":true,"origin":"","legend":"\u003cp\u003eTrial flowchart.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7896304/v1/d49e890062580dac82d415ce.png"},{"id":97148036,"identity":"8c884fd5-4bf1-4735-8b66-ba6bb67b11c5","added_by":"auto","created_at":"2025-12-01 10:17:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":80546,"visible":true,"origin":"","legend":"\u003cp\u003eRisk Stratification Analysis of Social Isolation and Hypertension\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7896304/v1/0782840b539666988f625314.png"},{"id":97147986,"identity":"a14849d0-5b3d-4306-8fe7-edc509f44c48","added_by":"auto","created_at":"2025-12-01 10:17:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":138765,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup analyses stratified by age, sex, race, marital status, and activity frequency\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7896304/v1/9f6a013b14bf231f4423d33b.png"},{"id":97147956,"identity":"69542954-4f92-414e-b6dc-ba08db37133b","added_by":"auto","created_at":"2025-12-01 10:17:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":56332,"visible":true,"origin":"","legend":"\u003cp\u003eThe AUC of the ROC curve results was 0.712.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7896304/v1/20ec817c65e09d8fa6db7a0d.png"},{"id":97148527,"identity":"4a265987-25c7-4ce2-a19b-0070d772b74d","added_by":"auto","created_at":"2025-12-01 10:18:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1442443,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7896304/v1/8a94330d-baea-4944-93bc-39d171b56024.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between hypertension and social isolation based on the ELSA database","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHypertension (HTN) is a clinical condition characterized by elevated systemic arterial blood pressure and is a major risk factor for damage to vital organs such as the heart, brain, and kidneys[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The 2023 WHO Global Report on Hypertension has highlighted concerning prevalence rates, estimating that by 2019, 1.3\u0026nbsp;billion adults worldwide were affected by HTN. Alarmingly, only 54% of cases were diagnosed, 42% received treatment, and a mere 21% achieved adequate blood pressure control[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As a major risk factor for cardiovascular diseases, HTN is a leading contributor to global morbidity and mortality. While effective treatment can reduce these risks, the current low rate of HTN control poses a significant challenge to achieving even lower blood pressure treatment targets. Thus, Therefore, urgent large-scale studies are imperative to systematically identify and assess HTN risk factors, facilitating the development of improved early intervention and precision treatment strategies.\u003c/p\u003e\u003cp\u003eThe concept of social isolation (SI) was initially introduced in 1979 to describe an objective condition marked by reduced social networks and absence of social ties. It occurs when an individual's social connections diminish notably in quantity and quality, leading to a significant decrease in social network size, interaction frequency, and relationship depth[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Survey data reveal that SI is a significant concern, affecting up to 25\u0026ndash;33% of older adults globally. With aging populations, rapid urbanization, and evolving social structures, the population vulnerable to SI is expanding[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. SI is a key risk factor for various neuropsychiatric conditions such as anxiety, depression, and cognitive decline, and is a strong predictor of physical health decline[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A prospective observational study demonstrated a direct link between SI and a 29% higher risk of mortality, a 29% increased risk of coronary heart disease, and a 32% elevated risk of stroke. Furthermore, a consistent association between SI and mortality risk is evident across countries with diverse levels of economic development[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While research on the relationship between SI and HTN remains limited in scope, existing studies have identified a robust link between the two. For example, a study conducted in the United States demonstrated that SI significantly raises the likelihood of developing HTN in young and early middle-aged adults, especially in men who are socially isolated from their family and friends[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These results suggest that social isolation\u0026mdash;a key psychosocial factor\u0026mdash;likely contributes significantly to the development of HTN. Additional research is needed to clarify the association between social isolation (SI) and HTN, offering new insights and approaches for preventing and managing HTN, with a focus on psychosocial support and lifestyle adjustments.\u003c/p\u003e\u003cp\u003eThe English Longitudinal Study of Ageing (ELSA) is a large-scale prospective cohort study focused on individuals aged 50 and above in England, overseen by institutions such as University College London[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Since its inception in 2002, data have been gathered by the research team biennially via comprehensive face-to-face interviews, self-administered questionnaires, physical assessments, and biomarker evaluations. The study encompasses vital domains including health status, physical capabilities, cognitive and mental well-being, social involvement, familial background, financial assets, and retirement arrangements[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Numerous investigations have leveraged the ELSA dataset. For example, one inquiry revealed a notable increase in the risk of depression among older adults, particularly in low- and middle-income nations, due to digital exclusion[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Another study reported no discernible link between initial dietary patterns and the development or advancement of coronary artery calcification.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] In essence, ELSA serves as a robust data repository for scrutinizing the enduring interplay of health and psychosocial elements in middle-aged and elderly cohorts, enabling thorough exploration of pivotal topics in gerontological research.\u003c/p\u003e\u003cp\u003eThis research examines the link between social isolation (SI) and hypertension (HTN) onset in individuals aged 50 and above in England, using longitudinal data from Wave 10 (2020\u0026ndash;2021) of the ELSA. The study seeks to offer empirical support for implementing social and behavioral interventions in the prevention and management of hypertension.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Data origin\u003c/h2\u003e\u003cp\u003eThe data is derived from the English Longitudinal Study of Ageing (ELSA) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.elsa-project.ac.uk\u003c/span\u003e\u003cspan address=\"https://www.elsa-project.ac.uk\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which targets individuals aged 50 or over and their partners, living in private households in England. Employing a stratified random sampling design, this study recruited a nationally representative sample of middle-aged and older participants, aiming to gain in-depth insights into the health, social, psychological, and economic aspects of population aging. The database contains detailed data collected from participants at regular intervals (approximately every two years), including in-person interviews, self-administered questionnaires, physical measurements, and biomarker tests. This study used wave 10 (2020\u0026ndash;2021) as the research baseline. The process of data acquisition and use strictly adhered to the approval requirements of the National Health Service (NHS) Research Ethics Committee in the UK, and all participants signed written informed consent forms.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Ascertainment of variables\u003c/h2\u003e\u003cp\u003eThe covariates include age (classified as \u0026gt;\u0026thinsp;65 years, \u0026le;\u0026thinsp;65 years) [DHAGE], sex (male and female) [DHSEX], ethnics (white/non-white) [FQETHNMR], marriage (married/single) [DIMARR], health (excellent/good/fair/bad/very bad) [HEHELF], activity frequency (hardly ever, or never/more than once a week/once a week/one to three times a month) [HEACTA], vision problems (blind/non-blind) [HEEYE], hearing problems (poor/non-poor) [HEHEAR], diabetes (with/without) [HEHaveDI], memory-related diseases (with/without) [HEHaveAD], and stroke (with/without) [HEEverST]. The outcome is hypertension (HTN) (with/without) [HEHaveBP], and the exposure factor is social isolation (SI) (yes or no) [PSCEDE] \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. In the ELSA database, the diagnostic criteria for the aforementioned variables (diabetes, memory-related diseases, stroke, and hypertension) are primarily based on self-reported physician diagnosis or self-reported information during follow-up assessments. Specifically, participants were asked the core question: \"Has a doctor ever told you that you have been diagnosed with diabetes, a memory-related disease, stroke, or hypertension?\". SI is defined such that participants score 1 point for each of the following criteria: being unmarried (including separated, divorced, widowed, or never married), having infrequent contact with their children (via telephone, in person, or email) on a weekly basis, and not participating in any social activities (including interacting with friends, playing chess or cards, and attending sports, social, or other clubs) in the past month. The social isolation index ranges from 0 to 3, with higher scores indicating a greater degree of social isolation. Participants with a score of \u0026ge;\u0026thinsp;1 were categorized into the socially isolated group[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] .\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eVariable and its number information table\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003elevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003evariable definition\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eData set and definition number\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eyear\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDHAGE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDHSEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRace\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-White\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFQETHNMR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhite\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMarriage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDIMARR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eHealth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eHEHELF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBad\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery bad\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eActivities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHardly ever, or never\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eHEACTA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMore than once a week\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOnce a week\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOne to three times a month\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVision_problems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-blind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHEEYE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBlind\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHearing_problems\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-poor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHEHEAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWithout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHEHaveDI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWith\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMemory_related_disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWithout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHEHaveAD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWith\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eContinued Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e Variable and its number information table\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eStroke\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWithout\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ecovariates\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHEEverST\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWith\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHTN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWithout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eoutcome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHEHaveBP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWith\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eexposure factor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePSCEDE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2020\u0026ndash;2021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Exclusion criteria\u003c/h2\u003e\u003cp\u003eThe exclusion criteria for this study were [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]participants with missing social isolation variables; participants whose covariates are marked as missing or rejected; participants who did not meet HTN or lack of information; participants with baseline age\u0026thinsp;\u0026lt;\u0026thinsp;50 years (ELSA lower limit of enrollment).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e\u003cp\u003eAll visualizations of charts in this research were performed using R software (v.5.2.3)[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The baseline analysis expressed categorical variables as percentages, used Pearson's chi-squared (χ\u003csup\u003e2\u003c/sup\u003e) tests to analyze differences between participants and various baseline characteristics, and the R package \"tableone\" (v 0.13.2) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] was used to draw the baseline table to complete the collation and presentation of relevant data. The statistical power for the difference in proportions between the two independent samples was calculated using the pwr package (v 1.3.0) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].The multinomial logistic regression model was used to construct the model, and the results are presented as adjusted odds ratios (ORs) and 95% confidence intervals (CIs) (p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Three models were constructed: model 1 did not adjust for any variables; model 2 adjusted for age, sex, and race (minimal adjustment model); model 3 further adjusted for marriage, health, activity frequency, vision problems, hearing problems, diabetes, memory-related diseases, and stroke (fully adjusted model). Additionally, the multinomial logistic regression model was used to analyze the association between SI and HTN in the three models and various variables. Univariate logistic regression analysis was used to analyze the association between SI and HTN in subgroups of sex, race, marital status, and activity frequency. The results were presented using the R packages \"tableone\" (v 0.13.2) and \"forestplot\" (v 3.1.1)[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Based on Model 3, the receiver operating characteristic (ROC\u0026thinsp;\u0026gt;\u0026thinsp;0.7) curve was plotted using the R package \u0026ldquo;pROC\u0026rdquo; (v 1.18.0) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] to analyze the predictive efficacy of SI on HTN risk and the predictive efficacy of HTN risk after model adjustment. The statistical significance level was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Baseline Characteristics of Participants\u003c/h2\u003e\u003cp\u003eThis study utilized data from the tenth wave (2020\u0026ndash;2021) of the ELSA database to summarize various variables for participants diagnosed with HTN, with 7589 participants. Based on the exclusion criteria, participants with missing variables related to social isolation were first excluded, leaving 7,100 participants (retention rate: 93.6%); participants with missing or refused covariates were then excluded, leaving 4,519 participants (retention rate: 59.5%); participants who did not meet the criteria for HTN or lacked relevant information were excluded, leaving 4,508 participants (retention rate: 59.4%); Finally, participants with a baseline age younger than 50 years were excluded, resulting in a final sample of 4,413 participants included in the analysis (retention rate: 58.1%). Participants were divided into a hypertension group (disease group) and a non-hypertension group (normal group) based on their hypertension status, with 1,607 participants in the disease group (157 reported loneliness, representing 9.77%) and 2,824 participants in the normal group (193 reported loneliness, accounting for 6.83%) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e The statistical power for the difference in proportions between the two independent samples was calculated. The results showed an effect size of Cohen\u0026rsquo;s h\u0026thinsp;=\u0026thinsp;0.107, with a significance level of α\u0026thinsp;=\u0026thinsp;0.05, corresponding to a statistical power of 92.8%, indicating that the sample size was sufficient to detect differences in proportions between the two groups. Further, a proportion test was conducted to examine the difference in loneliness proportions between the two groups. The results revealed a statistically significant difference (χ\u0026sup2; = 11.731, df\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;=\u0026thinsp;0.000615), with a 95% CI of (-0.0471, -0.0116). These findings suggest that the proportion of loneliness in the hypertension group was significantly higher than that in the normal group. The baseline characteristics of participants indicated that HTN was not associated with memory-related diseases, but was significantly associated with SI and other covariates. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipants ' baseline characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003elevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003econtrol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003edisease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2824\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1607\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSI(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2631 (93.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1450 (90.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e193 ( 6.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e157 ( 9.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAge (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1464 (51.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e508 (31.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1360 (48.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1099 (68.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSex (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1580 (55.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e716 (44.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1244 (44.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e891 (55.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eRace (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-White\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e166 ( 5.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e129 ( 8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhite\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2658 (94.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1478 (92.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMarriage (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2381 (84.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1401 (87.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e443 (15.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e206 (12.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eHealth (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e477 (16.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69 ( 4.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1029 (36.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e368 (22.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e828 (29.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e603 (37.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBad\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e371 (13.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e388 (24.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery bad\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e119 ( 4.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e179 (11.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eActivities (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHardly ever, or never\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1471 (52.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1078 (67.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMore than once a week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e823 (29.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e281 (17.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOnce a week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e296 (10.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e138 ( 8.6)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOne to three times a month\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e234 ( 8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e110 ( 6.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVision_problems (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enon-blind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2782 (98.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1559 (97.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eblind\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 ( 1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48 ( 3.0)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHearing_problems (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enon-poor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2734 (96.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1521 (94.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003epoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90 ( 3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86 ( 5.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ewithout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2655 (94.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1303 (81.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ewith\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e169 ( 6.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e304 (18.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eContinued Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e Baseline Characteristics of Participants\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003elevel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003econtrol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003edisease\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMemory_related_disease (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ewithout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2810 (99.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1592 (99.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ewith\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14 ( 0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e15 ( 0.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eStroke (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ewithout\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2760 (97.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1492 (92.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ewith\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64 ( 2.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e115 ( 7.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eValues are expressed as number (percentage) .\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Association analysis between SI and HTN risk\u003c/h2\u003e\u003cp\u003eThe association analysis between SI and HTN showed that SI was significantly associated with HTN in the three models ( OR\u0026thinsp;\u0026gt;\u0026thinsp;1, p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Among various variables, SI was also significantly associated with HTN ( p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, OR\u0026thinsp;=\u0026thinsp;1.287, 95% CI: 1.087\u0026ndash;1.524 ), which was a risk factor for increased prevalence of HTN. In addition, we also found that age, sex, race, and health status were significantly associated with the occurrence of HTN ( p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 ). These findings suggest that in the prevention and management of HTN, we should not only pay attention to the association between SI and HTN, but also integrate other related factors to effectively develop targeted interventions. \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRisk association analysis between social isolation and hypertension\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003emodel\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emodel 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.346\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.142\u0026ndash;1.587\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0004076\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emodel 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.212\u0026ndash;1.689\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.00002372\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emodel 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.287\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.087\u0026ndash;1.524\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003486\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eSI, social isolation\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.3 stratified analysis\u003c/h2\u003e\u003cp\u003eSubgroup analyses stratified by age, sex, race, marital status, and activity frequency revealed that SI was significantly associated with HTN in individuals aged 50 to 65 years, whereas this association was not significant in those aged\u0026thinsp;\u0026gt;\u0026thinsp;65 years. Regardless of sex (male or female) or marital status (married or single), SI showed a significant correlation with HTN. When considering race, the significant association between SI and HTN was exclusively observed among whites. Additionally, SI was significantly linked to HTN in individuals with hardly any or never physical activity \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The above results reveal the heterogeneity of the association between SI and HTN, suggesting that the role of SI in different populations may be regulated by factors such as age, race, and activity frequency, which provides a theoretical basis for future intervention strategies for specific populations.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.4 ROC analysis\u003c/h2\u003e\u003cp\u003eThe AUC of the ROC curve results was 0.712, which was greater than 0.7, indicating that SI had a good predictive ability for HTN, and the research results had a certain reference value \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discusion","content":"\u003cp\u003eHTN, a prevalent chronic condition globally known as the \"silent killer\" for its asymptomatic nature, poses a significant risk for severe cardiovascular complications, including acute coronary syndrome, aortic dissection, stroke, and renal failure [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Social isolation (SI) as a psychosocial factor may detrimentally affect blood pressure regulation through stress response activation, lifestyle behavior influence, and exacerbation of psychological distress, thereby closely intertwining with hypertension onset and progression[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This investigation leveraged Wave 10 (202\u0026ndash;2021) data from the ELSA database, employing chi-square (χ\u0026sup2;) tests, univariate and multivariate logistic regression analyses, as well as ROC curve analysis to explore the SI-hypertension relationship. The findings revealed a noteworthy association between SI and increased risk, establishing SI as a significant hypertension risk factor.\u003c/p\u003e\u003cp\u003eThe study establishes a significant correlation between social isolation (SI) and an elevated risk of hypertension (HTN), identifying SI as a risk factor for HTN, consistent with prior research. Notably, a study in the United States found that SI in young to middle-aged individuals substantially increased the likelihood of developing HTN. Another U.S. study investigated gender disparities in the link between SI and HTN among older adults, revealing that isolated men faced a higher risk of HTN compared to women, in whom no such association was observed [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The coherence of our results implies that the relationship between SI and HTN is not incidental but likely grounded in multiple underlying mechanisms. The consistency of our results with prior research suggests this relationship is not coincidental but rooted in biological and psychological mechanisms. For instance, animal studies provide compelling evidence that chronic social isolation can initiate or exacerbate chronic stress responses [\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], which subsequently activate the hypothalamic-pituitary-adrenal (HPA) axis and prompt the release of stress-related hormones such as glucocorticoids (predominantly cortisol) and angiotensin II[\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Furthermore, animal experiments demonstrate that SI amplifies inflammatory responses and increases the release of pro-inflammatory cytokines. These cytokines damage vascular endothelial cells, impeding vasodilation; they also stimulate vascular smoot muscle cell proliferation, thickening vessel walls, narrowing lumens, increasing vascular resistance, and ultimately elevating blood pressure [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Beyond biological pathways, SI often triggers negative emotions such as anxiety, depression, and loneliness, closely associated with HTN risk. Studies among Native American populations in the U.S. revealed that individuals with depressive symptoms had a 54% higher risk of developing HTN during follow-up compared to those without such symptoms. Similarly, depressive symptoms have been identified as a risk factor for HTN in young Hispanic/Latino adults. Additionally, a meta-analysis showed that anxiety is linked to an increased HTN risk[\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. These findings suggest that negative emotions induced by SI, such as depression and anxiety, may act as crucial mediators, persistently activating the body's stress response system, disrupting neuroendocrine regulation, ultimately contributing to elevated blood pressure, and serving as potential HTN risk factors.\u003c/p\u003e\u003cp\u003eTo investigate population-specific links between SI and HTN, this study conducted stratified analyses based on age, sex, race, marital status, and activity frequency. The results indicated varying strengths of association across different subgroups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), offering new insights into the contextual influences of SI on HTN and informing targeted preventive measures.The age-stratified analysis revealed a significant association between SI and HTN in the 50\u0026ndash;65 age group, whereas no significant correlation was observed in individuals aged\u0026thinsp;\u0026gt;\u0026thinsp;65 years. These results are consistent with prior U.S. studies focusing on younger to middle-aged cohorts, potentially linked to pivotal life transitions experienced by individuals in the middle age range. Social isolation in this demographic could induce psychological stress, activating the hypothalamic-pituitary-adrenal (HPA) axis and triggering the release of stress-related hormones, thereby increasing blood pressure[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Conversely, older adults may demonstrate heightened adaptability or the association between SI and HTN may be masked by concurrent health conditions. This finding implies that interventions addressing social isolation in the 50\u0026ndash;65 age group may be crucial for HTN prevention and management.\u003c/p\u003e\u003cp\u003eSI is a recognized risk factor for HTN that can be effectively addressed through multidimensional interventions aimed at mitigating its impact on blood pressure. Among high-risk populations, such as individuals aged 50\u0026ndash;65 years or those with little physical activity (consistent with our stratified findings), enhancing the frequency of virtual or in-person interactions-which are facilitated through video calls, social applications, or regular neighborly visits, can alleviate feelings of loneliness. Furthermore, promoting engagement in community group activities, such as social services or interest groups, has been associated with a reduction in inflammatory markers like IL-6[\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], directly counteracting the pro-inflammatory pathways linked to HTN in our mechanistic discussion. Studies have shown that physical exercise not only directly reduces blood pressure but also combats loneliness by fostering social interactions\u0026mdash;a key intervention for individuals with low activity levels, as their SI-HTN association was most pronounced. Moreover, dietary modifications, including decreasing sodium intake and increasing the consumption of fruits, vegetables, and low-fat dairy products, are more sustainable when individuals have robust social support networks, indirectly lowering the risk of HTN[\u003cspan additionalcitationids=\"CR45\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. In conclusion, future research should delve into tailored interventions for specific populations, such as 50-65-year-olds and sedentary individuals (given their stronger SI-HTN association). Enhancing collaboration between communities and families, leveraging technological advancements, and refining policies will be practical strategies to enhance the well-being and health outcomes of vulnerable groups.\u003c/p\u003e\u003cp\u003eThis study emphasizes a notable correlation between SI and a heightened likelihood of HTN, establishing SI as a predisposing factor for HTN. The findings offer insights into potential approaches for alleviating the disease burden and exploring causal factors, emphasizing the importance of comprehensive interventions to diminish SI in forthcoming endeavors. Nevertheless, the study is subject to certain limitations that warrant attention. Given that the data were derived from a publicly available database and exclusively focused on individuals aged 50 and older in England, the sample size is relatively restricted. Subsequent investigations could address this limitation by enlarging the sample size, including more diverse racial groups, and encompassing a wider age spectrum to bolster the generalizability of the findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval statement\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eEthical approval was not required for this study as it exclusively utilized publicly available data and/or previously published literature. No new data involving human or animal participants were collected for this analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient consent statement：\u003c/strong\u003ePatient consent \u0026nbsp;was not required for this study as it exclusively utilized publicly available data,No new data involving human or animal participants were collected for this analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eThe datasets generated and/or analysed during the currentstudy are available in\u0026nbsp;ELSA data,which are publicly available at[https://www.elsa-project.ac.uk]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests：\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding statement\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eFunding for this project was provided by the Ministry of Finance of China and National Health and Family Planning Commission, the Guangxi Key Laboratory of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention (22-035-18), Guangxi Clinical Research Center for Cardio-Cerebrovascular Diseases (AD17129014) and Guangxi Medical High-level Backbone Talents \"139\" Program (G201901006).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003eZLand XTconceived and designed the study. YS and GX\u0026nbsp;collected the data. YH and QJ\u0026nbsp;performed the statistical analysis. ZL and ZZ drafted the manuscript. All authors critically reviewed, edited, and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePilic, L., C.R. Pedlar, and Y. Mavrommatis, \u003cem\u003eSalt-sensitive hypertension: mechanisms and effects of dietary and other lifestyle factors.\u003c/em\u003e Nutr Rev, 2016. \u003cstrong\u003e74\u003c/strong\u003e(10): p. 645-58.DOI: 10.1093/nutrit/nuw028\u003c/li\u003e\n\u003cli\u003eGoorani, S., S. Zangene, and J.D. 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Ampey-Thornhill, \u003cem\u003eThe role of gender and family support on dietary compliance in an African American adolescent hypertension prevention study.\u003c/em\u003e Ann Behav Med, 2001. \u003cstrong\u003e23\u003c/strong\u003e(1): p. 59-67.DOI: 10.1207/s15324796abm2301_9\u003c/li\u003e\n\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":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"English Longitudinal Study of Ageing, Social Isolation, Hypertension","lastPublishedDoi":"10.21203/rs.3.rs-7896304/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7896304/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eHypertension (HTN) is a common cardiovascular disease (CVD) and a major contributor to disease burden and premature mortality worldwide. Social isolation (SI), as a significant social issue affecting health, is closely associated with the onset and progression of various diseases. However, there are relatively few studies that use HTN as an outcome variable. This study aims to clarify the association between SI and the onset and progression of HTN in middle-aged and older\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study is based on the 10th wave of the English Longitudinal Study of Ageing (ELSA) multi-wave longitudinal data. It employs chi-square (χ2) tests, multivariate logistic regression, univariate logistic regression, ROC curves, and other multidimensional analyses to explore the association between SI and HTN in middle-aged and older adults aged 50 and above.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe study found a significant association between SI and increased risk of HTN, making it a risk factor for HTN. In addition, stratified analysis found that SI was significantly associated with HTN in individuals aged 50 to 65 years, whereas this association was not significant in those aged\u0026thinsp;\u0026gt;\u0026thinsp;65 years. Regardless of sex (male or female) or marital status (married or single), SI showed a significant correlation with HTN. When considering race, the significant association between SI and HTN was exclusively observed among whites. Additionally, SI was significantly linked to HTN in individuals with hardly any or no physical activity.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eSI is an important risk factor for HTN, and its underlying causes are complex and diverse. Therefore, effective measures should be taken immediately to reduce SI.\u003c/p\u003e","manuscriptTitle":"Association between hypertension and social isolation based on the ELSA database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-01 10:09:06","doi":"10.21203/rs.3.rs-7896304/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-12-13T13:42:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"140046246863460229898804608784998952430","date":"2025-12-04T15:27:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-27T11:14:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-03T03:57:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-27T12:38:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-27T12:38:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2025-10-19T04:04:46+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"03133e96-0a07-44c3-91a8-4bfac6ee826d","owner":[],"postedDate":"December 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T10:09:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-01 10:09:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7896304","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7896304","identity":"rs-7896304","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}