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Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

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...

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Autores principales: Wang, Ke-Sheng, Liu, Xuefeng, Ategbole, Muyiwa, Xie, Xin, Liu, Ying, Xu, Chun, Xie, Changchun, Sha, Zhanxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: West Asia Organization for Cancer Prevention 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5720670/
https://www.ncbi.nlm.nih.gov/pubmed/28952708
http://dx.doi.org/10.22034/APJCP.2017.18.9.2581
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author Wang, Ke-Sheng
Liu, Xuefeng
Ategbole, Muyiwa
Xie, Xin
Liu, Ying
Xu, Chun
Xie, Changchun
Sha, Zhanxin
author_facet Wang, Ke-Sheng
Liu, Xuefeng
Ategbole, Muyiwa
Xie, Xin
Liu, Ying
Xu, Chun
Xie, Changchun
Sha, Zhanxin
author_sort Wang, Ke-Sheng
collection PubMed
description 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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spelling pubmed-57206702018-01-04 Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening Wang, Ke-Sheng Liu, Xuefeng Ategbole, Muyiwa Xie, Xin Liu, Ying Xu, Chun Xie, Changchun Sha, Zhanxin Asian Pac J Cancer Prev Research Article 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. West Asia Organization for Cancer Prevention 2017 /pmc/articles/PMC5720670/ /pubmed/28952708 http://dx.doi.org/10.22034/APJCP.2017.18.9.2581 Text en Copyright: © Asian Pacific Journal of Cancer Prevention http://creativecommons.org/licenses/BY-SA/4.0 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
spellingShingle Research Article
Wang, Ke-Sheng
Liu, Xuefeng
Ategbole, Muyiwa
Xie, Xin
Liu, Ying
Xu, Chun
Xie, Changchun
Sha, Zhanxin
Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening
title Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening
title_full Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening
title_fullStr Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening
title_full_unstemmed Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening
title_short Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening
title_sort generalized linear mixed model analysis of urban-rural differences in social and behavioral factors for colorectal cancer screening
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5720670/
https://www.ncbi.nlm.nih.gov/pubmed/28952708
http://dx.doi.org/10.22034/APJCP.2017.18.9.2581
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