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Haomiao Jia, Michael Link, J. Holt, A. Mokdad, Lei Li, P. Levy (2006)
Monitoring county-level vaccination coverage during the 2004-2005 influenza season.American journal of preventive medicine, 31 4
N. Krieger, Jarvis Chen, P. Waterman, Mah-Jabeen Soobader, S. Subramanian, Rosa Carson (2002)
Geocoding and monitoring of US socioeconomic inequalities in mortality and cancer incidence: does the choice of area-based measure and geographic level matter?: the Public Health Disparities Geocoding Project.American journal of epidemiology, 156 5
J. Eberth, M. Hossain, Jasmin Tiro, Xingyou Zhang, J. Holt, S. Vernon (2013)
Human papillomavirus vaccine coverage among females aged 11 to 17 in Texas counties: an application of multilevel, small area estimation.Women's health issues : official publication of the Jacobs Institute of Women's Health, 23 2
Z. Shun (1997)
Another Look at the Salamander Mating Data: A Modified Laplace Approximation ApproachJournal of the American Statistical Association, 92
C. Warshaw, Jonathan Rodden (2012)
How Should We Measure District-Level Public Opinion on Individual Issues?The Journal of Politics, 74
J. Rao (2003)
Small Area Estimation
J. Holt, Xingyou Zhang, L. Presley-Cantrell, J. Croft (2011)
Geographic disparities in chronic obstructive pulmonary disease (COPD) hospitalization among Medicare beneficiaries in the United StatesInternational Journal of Chronic Obstructive Pulmonary Disease, 6
G. Datta (2009)
Model-Based Approach to Small Area EstimationHandbook of Statistics, 29
T. Srebotnjak, A. Mokdad, C. Murray (2010)
A novel framework for validating and applying standardized small area measurement strategiesPopulation Health Metrics, 8
Jeffrey Lax, J. Phillips (2009)
How Should We Estimate Public Opinion in the StatesAmerican Journal of Political Science, 53
D. Xie, T. Raghunathan, J. Lepkowski (2007)
Estimation of the proportion of overweight individuals in small areas—a robust extension of the Fay–Herriot modelStatistics in Medicine, 26
Avis Thomas, L. Eberly, G. Smith, J. Neaton (2006)
ZIP-code-based versus tract-based income measures as long-term risk-adjusted mortality predictors.American journal of epidemiology, 164 6
Wenjun Li, T. Land, Zi Zhang, Lois Keithly, J. Kelsey (2009)
Small-area estimation and prioritizing communities for tobacco control efforts in Massachusetts.American journal of public health, 99 3
W. Bell, G. Datta, M. Ghosh (2013)
Benchmarking small area estimatorsBiometrika, 100
Zhen Zhang, Lei Zhang, A. Penman, Warren May (2011)
Using Small-Area Estimation Method to Calculate County-Level Prevalence of Obesity in Mississippi, 2007-2009Preventing Chronic Disease, 8
Casey Olives, R. Myerson, A. Mokdad, C. Murray, Stephen Lim (2013)
Prevalence, Awareness, Treatment, and Control of Hypertension in United States Counties, 2001–2009PLoS ONE, 8
Y. Marhuenda, I. Molina, D. Morales (2013)
Small area estimation with spatio-temporal Fay-Herriot modelsComput. Stat. Data Anal., 58
Haomiao Jia, P. Muennig, E. Borawski (2004)
Comparison of small-area analysis techniques for estimating county-level outcomes.American journal of preventive medicine, 26 5
Karen Schneider, K. Lapane, M. Clark, W. Rakowski (2009)
Using Small-Area Estimation to Describe County-Level Disparities in MammographyPreventing Chronic Disease, 6
A. Earnest, J. Beard, G. Morgan, D. Lincoln, R. Summerhayes, D. Donoghue, Therese Dunn, D. Muscatello, K. Mengersen (2010)
Small area estimation of sparse disease counts using shared component models-application to birth defect registry data in New South Wales, Australia.Health & place, 16 4
Wenjun Li, J. Kelsey, Zi Zhang, S. Lemon, Solomon Mezgebu, C. Boddie-Willis, G. Reed (2009)
Small-area estimation and prioritizing communities for obesity control in Massachusetts.American journal of public health, 99 3
M. Goodman (2010)
Comparison of Small-Area Analysis Techniques for Estimating Prevalence by RacePreventing Chronic Disease, 7
B. Cadwell, T. Thompson, J. Boyle, L. Barker (2010)
Bayesian Small Area Estimates of Diabetes Prevalence by U.S. County, 2005
David Park, A. Gelman, Joseph Bafumi (2004)
Bayesian Multilevel Estimation with Poststratification: State-Level Estimates from National PollsPolitical Analysis, 12
A. Miniño (2011)
Death in the United States, 2009.NCHS data brief, 64
Peter Congdon (2009)
International Journal of Health Geographics Open Access a Multilevel Model for Cardiovascular Disease Prevalence in the Us and Its Application to Micro Area Prevalence Estimates
A variety of small-area statistical models have been developed for health surveys, but none are sufficiently flexible to generate small-area estimates (SAEs) to meet data needs at different geographic levels. We developed a multilevel logistic model with both state- and nested county-level random effects for chronic obstructive pulmonary disease (COPD) using 2011 data from the Behavioral Risk Factor Surveillance System. We applied poststratification with the (decennial) US Census 2010 counts of census-block population to generate census-block-level SAEs of COPD prevalence which could be conveniently aggregated to all other census geographic units, such as census tracts, counties, and congressional districts. The model-based SAEs and direct survey estimates of COPD prevalence were quite consistent at both the county and state levels. The Pearson correlation coefficient was 0.99 at the state level and ranged from 0.88 to 0.95 at the county level. Our extended multilevel regression modeling and poststratification approach could be adapted for other geocoded national health surveys to generate reliable SAEs for population health outcomes at all administrative and legislative geographic levels of interest in a scalable framework.
American Journal of Epidemiology – Oxford University Press
Published: Apr 15, 2014
Keywords: Behavioral Risk Factor Surveillance System chronic obstructive pulmonary disease multilevel regression and poststratification population health outcomes small-area estimation
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