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Association of group-level segregation with cardiovascular health in older adults: an analysis of data from the Korean Social Life, Health, and Aging Project
Sung-Ha Lee, Hyeok-Hee Lee, Kiho Sung, Yoosik Youm, Hyeon Chang Kim
Epidemiol Health. 2023;45:e2023041.   Published online April 4, 2023
DOI: https://doi.org/10.4178/epih.e2023041
  • 5,469 View
  • 187 Download
  • 1 Web of Science
  • 1 Crossref
AbstractAbstract AbstractSummary PDFSupplementary Material
Abstract
OBJECTIVES
The adverse health effects of individual-level social isolation (e.g., perceived loneliness) have been well documented in older adults. However, little is known about the impact of collective-level social isolation on health outcomes. We sought to examine the association of group-level segregation with cardiovascular health (CVH) in older adults.
METHODS
From the prospective Korean Social Life, Health, and Aging Project database, we identified 528 community-dwelling older adults who were aged ≥60 years or were married to those aged ≥60 years. Participants who belonged to smaller social groups separate from the major social group were defined as group-level-segregated. The CVH score was calculated as the number of ideal non-dietary CVH metrics (0-6), as modified from the American Heart Association’s Life’s Simple 7. Using ordinal logistic regression models, we assessed cross-sectional and longitudinal associations between group-level segregation and CVH.
RESULTS
Of the 528 participants (mean age, 71.7 years; 60.0% female), 108 (20.5%) were segregated at baseline. In the crosssectional analysis, group-level segregation was significantly associated with lower odds of having a higher CVH score at baseline after adjusting for socio-demographic factors and cognitive function (odds ratio [OR], 0.64; 95% confidence interval [CI], 0.43 to 0.95). Among 274 participants who completed an 8-year follow-up, group-level segregation at baseline was marginally associated with lower odds of having a higher CVH score at 8 years (OR, 0.49; 95% CI, 0.24 to 1.02).
CONCLUSIONS
Group-level segregation was associated with worse CVH. These findings imply that the social network structure of a community may influence its members’ health status.
Summary
Korean summary
본 연구는 “한국인의 사회적 삶, 건강과 노화에 대한 조사”(Korean Social Life, Health and Aging Project, KSHAP)에서 측정한 한 지역 내의 사회적 연결망 자료를 이용하여 사회적 분리와 심혈관 건강 사이의 관계를 살펴보았다. 그 결과, 사회적 분리는 비만, 고혈압, 콜레스테롤, 흡연, 음주 신체적 활동 등을 종합한 ‘라이프 심플 7’ 지표와 부정적인 관련성을 보였으며, 8년 후 추적 조사에서도 이 패턴이 유지되었다. 본 연구 결과는 사회적, 집단적 분리 현상이 신체적 건강에도 악영향을 초래할 수 있음을 시사한다.
Key Message
Using the prospective Korean Social Life, Health, and Aging Project (KSHAP) database, we discovered that group-level segregation was significantly associated with worse cardiovascular health (CVH). Also, we observed a tendency for baseline group-level segregation to be linked to worse CVH after an 8-year follow-up period. These findings emphasize the significance of group-level segregation as a potential contributing factor in the health outcomes of older adults.

Citations

Citations to this article as recorded by  
  • Association of social isolation and loneliness with the risk of hypertension in middle aged and older adults: Findings from a national representative longitudinal survey
    Shiqi Wang, Hao Zhang, Yiling Lou, Qiqi You, Qingqing Jiang, Shiyi Cao
    Journal of Affective Disorders.2024; 349: 577.     CrossRef
Reconstructing a COVID-19 outbreak within a religious group using social network analysis simulation in Korea
Namje Kim, Su Jin Kang, Sangwoo Tak
Epidemiol Health. 2021;43:e2021068.   Published online September 16, 2021
DOI: https://doi.org/10.4178/epih.e2021068
  • 8,998 View
  • 216 Download
  • 4 Web of Science
  • 4 Crossref
AbstractAbstract AbstractSummary PDF
Abstract
OBJECTIVES
We reconstructed a coronavirus disease 2019 (COVID-19) outbreak to examine how a large cluster at a church setting spread before being detected and estimate the potential effectiveness of complying with mask-wearing guidelines recommended by the government.
METHODS
A mathematical model with a social network analysis (SNA) approach was used to simulate a COVID-19 outbreak. A discrete-time stochastic simulation model was used to simulate the spread of COVID-19 within the Sarang Jeil church. A counterfactual experiment using a calibrated baseline model was conducted to examine the potential benefits of complying with a mask-wearing policy.
RESULTS
Simulations estimated a mask-wearing ratio of 67% at the time of the outbreak, which yielded 953.8 (95% confidence interval [CI], 937.3 to 970.4) cases and was most consistent with the confirmed data. The counterfactual experiment with 95% mask-wearing estimated an average of 45.6 (95% CI, 43.4 to 47.9) cases with a standard deviation of 20.1. The result indicated that if the church followed government mask-wearing guidelines properly, the outbreak might have been one-twentieth the size.
CONCLUSIONS
SNA is an effective tool for monitoring and controlling outbreaks of COVID-19 and other infectious diseases. Although our results are based on simulations and are thus limited, the precautionary implications of social distancing and mask-wearing are still relevant. Since person-to-person contacts and interactions are unavoidable in social and economic life, it may be beneficial to develop precise measures and guidelines for particular organizations or places that are susceptible to cluster outbreaks.
Summary
Korean summary
본 연구는 구조화된 확률적 네트워크 시뮬레이션모형을 이용하여 국내에서 발생했던 사랑제일교회 발 코로나19 집단 감염 사례의 일별 확진자 데이터를 설명하고자, 마스크 착용 비율 추정과 반사실적 실험을 통해 방역지침을 준수한 경우 발생할 수 있었을 확진자의 규모를 추정하였다. 시뮬레이션 결과 추정된 당시 사랑제일교회의 마스크 착용 비율은 약 67% 수준이며, 만약 참석자의 95%가 마스크를 착용한 경우 확진자 규모는 실제의 20분의 1 수준에 그쳤을 것으로 예상된다. 마스크 착용은 예방접종과 함께 코로나 감염증을 극복하기 위한 가장 효과적인 예방활동이며 가장 마지막까지 강조되어야 할 것이다.
Key Message
To better understand the transmission of COVID-19 in a church setting, a stochastic social network analysis with a focus on mask-wearing practice was constructed. The results showed that if mask-wearing were to increase from 67% (at the time of the outbreak) to 95%, the outbreak could have been one-twentieth the size. Among the many measures of non-pharmaceutical intervention which may be withdrawn, mask-wearing is still one of the most effective precautionary measure and should continue to be emphasized.

Citations

Citations to this article as recorded by  
  • Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature
    Hyojung Lee, Sol Kim, Minyoung Jeong, Eunseo Choi, Hyeonjeong Ahn, Jeehyun Lee
    Yonsei Medical Journal.2023; 64(1): 1.     CrossRef
  • A Social Network Analysis Approach to Evaluate the Relationship Between the Mobility Network Metrics and the COVID-19 Outbreak
    Sadegh Ilbeigipour, Babak Teimourpour
    Health Services Insights.2023; 16: 117863292311738.     CrossRef
  • The effect of shortening the quarantine period and lifting the indoor mask mandate on the spread of COVID-19: a mathematical modeling approach
    Jung Eun Kim, Heejin Choi, Minji Lee, Chang Hyeong Lee
    Frontiers in Public Health.2023;[Epub]     CrossRef
  • Investigation of Statistical Machine Learning Models for COVID-19 Epidemic Process Simulation: Random Forest, K-Nearest Neighbors, Gradient Boosting
    Dmytro Chumachenko, Ievgen Meniailov, Kseniia Bazilevych, Tetyana Chumachenko, Sergey Yakovlev
    Computation.2022; 10(6): 86.     CrossRef
The anatomy of COVID-19 comorbidity networks among hospitalized Korean patients
Eun Kyong Shin, Hyo Young Choi, Neil Hayes
Epidemiol Health. 2021;43:e2021035.   Published online May 7, 2021
DOI: https://doi.org/10.4178/epih.e2021035
  • 11,337 View
  • 381 Download
  • 3 Web of Science
  • 3 Crossref
AbstractAbstract AbstractSummary PDF
Abstract
OBJECTIVES
We aimed to examine how comorbidities were associated with outcomes (illness severity or death) among hospitalized patients with coronavirus disease 2019 (COVID-19).
METHODS
Data were provided by the National Medical Center of the Korea Disease Control and Prevention Agency. These data included the clinical and epidemiological information of all patients hospitalized with COVID-19 who were discharged on or before April 30, 2020 in Korea. We conducted comorbidity network and multinomial logistic regression analyses to identify risk factors associated with COVID-19 disease severity and mortality. The outcome variable was the clinical severity score (CSS), categorized as mild (oxygen treatment not needed), severe (oxygen treatment needed), or death.
RESULTS
In total, 5,771 patients were included. In the fully adjusted model, chronic kidney disease (CKD) (odds ratio [OR], 2.58; 95% confidence interval [CI], 1.19 to 5.61) and chronic obstructive pulmonary disease (COPD) (OR, 3.19; 95% CI, 1.35 to 7.52) were significantly associated with disease severity. CKD (OR, 5.35; 95% CI, 2.00 to 14.31), heart failure (HF) (OR, 3.15; 95% CI, 1.22 to 8.15), malignancy (OR, 3.38; 95% CI, 1.59 to 7.17), dementia (OR, 2.62; 95% CI, 1.45 to 4.72), and diabetes mellitus (OR, 2.26; 95% CI, 1.46 to 3.49) were associated with an increased risk of death. Asthma and hypertension showed statistically insignificant associations with an increased risk of death.
CONCLUSIONS
Underlying diseases contribute differently to the severity of COVID-19. To efficiently allocate limited medical resources, underlying comorbidities should be closely monitored, particularly CKD, COPD, and HF.
Summary
Korean summary
본 연구는 2019 년 코로나 바이러스 질환 (COVID-19)으로 입원 한 환자의 합병증이 결과 (질병 중증도 또는 사망)와 어떤 관련이 있는지를 동반 질환 네트워크 및 다항 로지스틱 회귀 분석을 통해 분석하였다. 기저 질환은 COVID-19의 중증도 및 사망에 차별적으로 영향을 미친다. 제한된 의료 자원을 효율적으로 활용하기 위해서 환자의 기저 동반 질환 중, 특히 만성 신장 질환 (CKD), 만성 폐쇄성 폐 질환 (COPD), 심부전 (HF)을 더욱 면밀히 모니터링해야 한다.
Key Message
We examined how comorbidities were associated with outcomes (illness severity or death) among hospitalized patients with coronavirus disease 2019 (COVID-19), implementing comorbidity network and multinomial logistic regression analyses. Underlying diseases contribute differently to the severity of COVID-19. To efficiently allocate limited medical resources, underlying comorbidities should be closely monitored, particularly chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), and heart failure (HF).

Citations

Citations to this article as recorded by  
  • SARS-CoV-2 susceptibility and COVID-19 illness course and outcome in people with pre-existing neurodegenerative disorders: systematic review with frequentist and Bayesian meta-analyses
    Muhannad Smadi, Melina Kaburis, Youval Schnapper, Gabriel Reina, Patricio Molero, Marc L. Molendijk
    The British Journal of Psychiatry.2023; 223(2): 348.     CrossRef
  • Asthma and COPD as co-morbidities in patients hospitalised with Covid-19 disease: a global systematic review and meta-analysis
    James Patrick Finnerty, A. B. M. Arad Hussain, Aravind Ponnuswamy, Hafiz Gulzeb Kamil, Ammar Abdelaziz
    BMC Pulmonary Medicine.2023;[Epub]     CrossRef
  • The Role of Diabetes and Hyperglycemia on COVID-19 Infection Course—A Narrative Review
    Evangelia Tzeravini, Eleftherios Stratigakos, Chris Siafarikas, Anastasios Tentolouris, Nikolaos Tentolouris
    Frontiers in Clinical Diabetes and Healthcare.2022;[Epub]     CrossRef

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