Spelling suggestions: "subject:"urbanrural differences"" "subject:"urbanorural differences""
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Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer ScreeningWang, Ke Sheng, Liu, Xuefeng, Ategbole, Muyiwa, Xie, Xin, Liu, Ying, Xu, Chun, Xie, Changchun, Sha, Zhanxin 01 September 2017 (has links)
Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p < 0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p < 0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p < 0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions.
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班級同儕學習投入與數學表現的城鄉差距 —階層線性模型的分析 / Urban-rural differences in peer engagement and mathematics performance: an analysis of hierarchical linear modeling林靜怡 Unknown Date (has links)
學習表現為教育社會學中的重要議題,其中城鄉間的學習表現差距受到重視。過去研究認為家庭背景與地區的教育資源是影響學生學習表現的主要因素,然而這些研究缺乏班級因素與同儕效果的分析。因此本研究使用台灣教育長期追蹤資料庫(Taiwan Education Panel Survey, TEPS)在2001年與2003年的國中生樣本,以階層線性模型(Hierarchical Linear Modeling, HLM)分析國一班級同儕學習投入對國三數學表現的影響,學習投入以學生為課業所付出的時間為指標。分析結果發現:(1)學生數學表現的總變異中有24%來自班級因素的影響,76%為學生因素。(2)國三數學表現、個人學習投入與班級同儕學習投入有城鄉差距。(3)在控制其他變項下,個人學習投入、班級同儕學習投入對數學表現有正向效果。(4)班級所在地區的都市化程度透過班級同儕學習投入間接影響國三數學表現。 / Academic performance has been an important topic of research on educational sociology for a long time, while urban-rural differences have been already well documented in literatures. In the past, the literature indicated that the key factors to affecting academic performance are family background and the educational resources. But these researches have ignored the factors of class level and peer effects. In this study, the data are from Taiwan Education Panel Survey (TEPS) in 2001 and 2003, use Hierarchical Linear Modeling (HLM) to assess how peer engagement affects junior high students’ mathematics performance. The time students spend in studying is an index of engagement. The main finding are: (1) This research model accounts for 76% of the variation in student level and for 24% of the class variation in class level with regard to mathematical performance. (2) Students in the urban and rural city show a differences in their mathematics performance, student’s own engagement and peer engagement. (3) When controlling variables, student’s own engagement and peer engagement have positive effect on mathematics performance. (4) Urbanization levels indirectly affect mathematics performance through peer engagement.
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Exploring the hidden impact of the Covid-19 pandemic: The role of urbanizationArin, K. Peren, Lacomba, Juan A., Lagos, Francisco, Moro-Egido, Ana I., Thum, Marcel 05 June 2023 (has links)
We examine the role of residential environments (urban/rural) in understanding the impact of the COVID-19 pandemic and the restrictions in nationwide movement on several socio-economic attitudes. We conducted large-scale surveys in four European countries (France, Germany, Spain, and the United Kingdom) before and after nationwide lockdowns were implemented. We investigate how the pandemic affected: (i) economic (economic insecurity), (ii) political (trust in domestic and international institutions), and (iii) social attitudes (loneliness), by controlling for the degree of urbanization, obtained from the geocodes of the survey respondents. Our results show that taking the degree of urbanization into account is not only relevant but is also essential. Compared to urban areas, in rural areas lockdowns led to a greater increase of economic insecurity and to a greater decrease in trust in domestic institutions. We also show that these results are particularly valid for women and households with children.
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