ArticlePreventing chronic disease2016
A Methodological Approach to Small Area Estimation for the Behavioral Risk Factor Surveillance System.
Article in Preventing chronic disease, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Longitudinal Spatial Analysis of Health-Related Quality of Life in Mississippi: Clustering, Trends, and Socioeconomic Drivers.Preventing chronic disease · 2026Article
- Association Between Observed Climate Change and Cardiovascular Disease in the United States.GeoHealth · 2026Article
- Estimating county-level dental care utilization among adults in California using multilevel modeling with raking approach.Archives of public health = Archives belges de sante publique · 2025Article
- Antimicrobial-Resistant Infections in Hospitalized Patients.JAMA network open · 2025Article
- Adverse Childhood Experiences Among U.S. Adults: National and State Estimates by Adversity Type, 2019-2020.American journal of preventive medicine · 2024Article
- Building towards an adolescent neural urbanome: Expanding environmental measures using linked external data (LED) in the ABCD study.Developmental cognitive neuroscience · 2024Article
- Estimating County Level Health Indicators Using Spatial Microsimulation.Population, space and place · 2023Article
- Re-scaling and small area estimation of behavioral risk survey guided by social vulnerability data.BMC public health · 2023Article
- Hierarchical Bayes small area estimation for county-level health prevalence to having a personal doctor.Statistical methods & applications · 2022Article
- PLACES: Local Data for Better Health.Preventing chronic disease · 2022Article
- 'Hybrid Survey' approach to non-communicable disease surveillance in the US-Affiliated Pacific Islands.BMJ global health · 2021Article
- Small area estimation and childhood obesity surveillance using electronic health records.PloS one · 2021Article
- Use of Small-Area Estimates to Describe County-Level Geographic Variation in Prevalence of Extreme Obesity Among US Adults.JAMA network open · 2020Article
- Multidrug-Resistant Bacterial Infections in U.S. Hospitalized Patients, 2012-2017.The New England journal of medicine · 2020Article
- Small Area Estimation of Mental Distress Among United States Military Veterans in Illinois.Community mental health journal · 2020Article
- INCORPORATING DESIGN WEIGHTS AND HISTORICAL DATA INTO MODEL-BASED SMALL-AREA ESTIMATION.Journal of data science : JDS · 2020Article
- Small Area Estimation of Cancer Risk Factors and Screening Behaviors in US Counties by Combining Two Large National Health Surveys.Preventing chronic disease · 2019Article
- Socioeconomic And Survival Differences Among Minorities With Hepatocellular Carcinoma In Florida.Journal of hepatocellular carcinoma · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Public health researchers have used a class of statistical methods to calculate prevalence estimates for small geographic areas with few direct observations. Many researchers have used Behavioral Risk Factor Surveillance System (BRFSS) data as a basis for their models. The aims of this study were to 1) describe a new BRFSS small area estimation (SAE) method and 2) investigate the internal and external validity of the BRFSS SAEs it produced. The BRFSS SAE method uses 4 data sets (the BRFSS, the American Community Survey Public Use Microdata Sample, Nielsen Claritas population totals, and the Missouri Census Geographic Equivalency File) to build a single weighted data set. Our findings indicate that internal and external validity tests were successful across many estimates. The BRFSS SAE method is one of several methods that can be used to produce reliable prevalence estimates in small geographic areas.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.