Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys
BACKGROUND: National health surveys, such as the National Health Interview Survey (NHIS) and the Behavioral Risk Factor Surveillance System (BRFSS), collect data on cancer screening and smoking-related measures in the US noninstitutionalized population. These surveys are designed to produce reliable...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Centers for Disease Control and Prevention
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6716412/ https://www.ncbi.nlm.nih.gov/pubmed/31469068 http://dx.doi.org/10.5888/pcd16.190013 |
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author | Liu, Benmei Parsons, Van Feuer, Eric J. Pan, Qiang Town, Machell Raghunathan, Trivellore E. Schenker, Nathaniel Xie, Dawei |
author_facet | Liu, Benmei Parsons, Van Feuer, Eric J. Pan, Qiang Town, Machell Raghunathan, Trivellore E. Schenker, Nathaniel Xie, Dawei |
author_sort | Liu, Benmei |
collection | PubMed |
description | BACKGROUND: National health surveys, such as the National Health Interview Survey (NHIS) and the Behavioral Risk Factor Surveillance System (BRFSS), collect data on cancer screening and smoking-related measures in the US noninstitutionalized population. These surveys are designed to produce reliable estimates at the national and state levels. However, county-level data are often needed for cancer surveillance and related research. METHODS: To use the large sample sizes of BRFSS and the high response rates and better coverage of NHIS, we applied multilevel models that combined information from both surveys. We also used relevant sources such as census and administrative records. By using these methods, we generated estimates for several cancer risk factors and screening behaviors that are more precise than design-based estimates. RESULTS: We produced reliable, modeled estimates for 11 outcomes related to smoking and to screening for female breast cancer, cervical cancer, and colorectal cancer. The estimates were produced for 3,112 counties in the United States for the data period from 2008 through 2010. CONCLUSION: The modeled estimates corrected for potential noncoverage bias and nonresponse bias in the BRFSS and reduced the variability in NHIS estimates that is attributable to small sample size. The small area estimates produced in this study can serve as a useful resource to the cancer surveillance community. |
format | Online Article Text |
id | pubmed-6716412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Centers for Disease Control and Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-67164122019-09-06 Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys Liu, Benmei Parsons, Van Feuer, Eric J. Pan, Qiang Town, Machell Raghunathan, Trivellore E. Schenker, Nathaniel Xie, Dawei Prev Chronic Dis Original Research BACKGROUND: National health surveys, such as the National Health Interview Survey (NHIS) and the Behavioral Risk Factor Surveillance System (BRFSS), collect data on cancer screening and smoking-related measures in the US noninstitutionalized population. These surveys are designed to produce reliable estimates at the national and state levels. However, county-level data are often needed for cancer surveillance and related research. METHODS: To use the large sample sizes of BRFSS and the high response rates and better coverage of NHIS, we applied multilevel models that combined information from both surveys. We also used relevant sources such as census and administrative records. By using these methods, we generated estimates for several cancer risk factors and screening behaviors that are more precise than design-based estimates. RESULTS: We produced reliable, modeled estimates for 11 outcomes related to smoking and to screening for female breast cancer, cervical cancer, and colorectal cancer. The estimates were produced for 3,112 counties in the United States for the data period from 2008 through 2010. CONCLUSION: The modeled estimates corrected for potential noncoverage bias and nonresponse bias in the BRFSS and reduced the variability in NHIS estimates that is attributable to small sample size. The small area estimates produced in this study can serve as a useful resource to the cancer surveillance community. Centers for Disease Control and Prevention 2019-08-29 /pmc/articles/PMC6716412/ /pubmed/31469068 http://dx.doi.org/10.5888/pcd16.190013 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited. |
spellingShingle | Original Research Liu, Benmei Parsons, Van Feuer, Eric J. Pan, Qiang Town, Machell Raghunathan, Trivellore E. Schenker, Nathaniel Xie, Dawei Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys |
title | Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys |
title_full | Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys |
title_fullStr | Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys |
title_full_unstemmed | Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys |
title_short | Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys |
title_sort | small area estimation of cancer risk factors and screening behaviors in us counties by combining two large national health surveys |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6716412/ https://www.ncbi.nlm.nih.gov/pubmed/31469068 http://dx.doi.org/10.5888/pcd16.190013 |
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