Objectives This study aimed to investigate the combined effects of individual, household, and community-level factors on coronavirus disease 2019 (COVID-19) vaccination intention using a multilevel analysis. Methods: This cross-sectional study analyzed raw data from the 2021 Korea Community Health Survey and regional statistics from 255 health centers, with a final sample of 229,216 individuals. Multilevel analysis was conducted, focusing on individual, household, and community-level factors. Individual-level factors included demographics, health status, and COVID-19 concerns; household-level factors included income and marital status; and community-level factors included city type and vaccination rates. Results: At the individual level, significant differences were observed across all variables. At the household level, higher vaccination intention was associated with households of 4 or more members and a monthly income of 4 million Korean won or more. At the community level, higher flu vaccination rates, greater concern about COVID-19 infection, and higher COVID-19 vaccination rates were linked to increased vaccination intention. Conclusion: This study highlights that COVID-19 vaccination intention is influenced by factors at the individual, household, and community levels. Vaccination strategies that integrate household and community-level approaches may be more effective. Policymakers should consider both individual and social health factors when designing vaccination policies.
Objectives Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. Methods: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk. Results: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02–1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42– 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07–2.69), travel history (aOR, 2.30; 95% CI, 1.13–4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72–0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16– 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97–0.99) were significant determinants. Conclusion: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.
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Age-stratified epidemiological and clinical predictors of laboratory-confirmed measles among suspected cases in Diyarbakır, Türkiye (2012–2024): a test-negative case–control study Derya Çağlayan, Ahmet Yusuf Çakırci̇, Hasip Kahraman, Çınar Demir Aktar, Ruken Turhan, Ömer Faruk Şeker, Mehmet Hakan Pamukçu, Murat Can, Hanife Hilal Andan BMC Infectious Diseases.2026;[Epub] CrossRef
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<title>Objectives</title>
<p>In this study the relationship between neighborhood deprivation and the unmet health care needs of elderly individuals (≥ 65 years) was examined. Some previous studies suggested that neighborhood characteristics affect access to health care, yet research on the unmet needs of older individuals is limited.</p></sec>
<sec>
<title>Methods</title>
<p>Multilevel logistic regression analysis was used to assess the relationship of neighborhood-level factors with unmet health care needs due to costs, adjusting for individual-level factors, in individuals ≥ 65 years in the 2017 Korean Community Health Survey (<italic>n</italic> = 63,388).</p></sec>
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<title>Results</title>
<p>There were 2.6% of elderly individuals who experienced unmet health care needs due to costs. Following adjustment for individual and neighborhood characteristics, the neighborhood deprivation in urban areas was found to have an inverse association with unmet needs (odds ratio = 0.50; 95% confidence interval = 0.24–1.06) for the most deprived quartile versus the least deprived quartile). However, in rural areas neighborhood deprivation was not a significant variable. Among the individual-level variables, household income was one of the strongest correlates with unmet needs in both urban and rural areas.</p></sec>
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<title>Conclusion</title>
<p>The present findings suggest that targeted policy interventions reflecting both neighborhood and individual characteristics, should be implemented to reduce the unmet health care needs of elderly individuals.</p></sec>
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<sec>
<title>Objectives</title>
<p>This study investigates investigated the relationship between social and physical environments, and moderate to vigorous physical activity (MVPA) amongst adults in both rural and urban areas within Korea.</p></sec>
<sec>
<title>Methods</title>
<p>A sample of 128,735 adults from the 2013 Community Health Survey (CHS) was analyzed using a multilevel logistic analysis.</p></sec>
<sec>
<title>Results</title>
<p>Urban residents with higher satisfaction in public transportation satisfaction and rural residents with more access to sports parks, hiking trails, and bike cycle paths were more likely to be active. The MVPA of adults from rural areas correlated urban adults was uncorrelatedwith neighborhood factors, but that of rural adults was whereas no correlations were observed in adults from urban areas.</p></sec>
<sec>
<title>Conclusion</title>
<p>These differences should be considered when developing interventions strategies to enhance adult physical activity in different communities.</p></sec>
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