Validation of multilevel regression and poststratification methodology for small area estimation of health indicators from the behavioral risk factor surveillance system

Periodontitis prevalence in adults ≥ 65 years of age, in the USA

The older adult population is growing rapidly in the USA and it is expected that by 2040 the number of adults ≥ 65 years of age will have increased by about 50%. With the growth of this subpopulation, oral health status, and periodontal status in particular, becomes important in the quest to maintain an adequate quality of life. Poor oral health can have a major impact, leading to tooth loss, pain and discomfort, and may prevent older adults from chewing food properly, often leading to poor nutrition. Periodontitis is monitored in the USA at the national level as part of the Healthy People 2020 initiative. In this report, we provide estimates of the overall burden of periodontitis among adults ≥ 65 years of age and after stratification according to sociodemographic factors, modifiable risk factors (such as smoking status), the presence of other systemic conditions (such as diabetes) and access to dental care. We also estimated the burden of periodontitis within this age group at the state and local levels. Data from the National Health and Nutrition Examination Survey 2009/2010 and 2011/2012 cycles were analyzed. Periodontal measures from both survey cycles were based on a full-mouth periodontal examination. Nineteen per cent of adults in this subpopulation were edentulous. The mean age was 73 years, 7% were current smokers, 8% lived below the 100% Federal Poverty Level and < 40% had seen a dentist in the past year. Almost two-thirds (62.3%) had one or more sites with ≥ 5 mm of clinical attachment loss and almost half had at least one site with probing pocket depth of ≥ 4 mm. We estimated the lowest prevalence of periodontitis in Utah (62.3%) and New Hampshire (62.6%) and the highest in New Mexico, Hawaii, and the District of Columbia each with a prevalence of higher than 70%. Overall, periodontitis is highly prevalent in this subpopulation, with two-thirds of dentate older adults affected at any geographic level. These findings provide an opportunity to determine how the overall health-care management of older adults should consider the improvement of their oral health conditions. Many older adults do not have dental insurance and are also likely to have some chronic conditions, which can adversely affect their oral health.

Comparison of Methods for Estimating Prevalence of Chronic Diseases and Health Behaviors for Small Geographic Areas: Boston Validation Study, 2013

Introduction

Local health authorities need small-area estimates for prevalence of chronic diseases and health behaviors for multiple purposes. We generated city-level and census-tract–level prevalence estimates of 27 measures for the 500 largest US cities.

Methods

To validate the methodology, we constructed multilevel logistic regressions to predict 10 selected health indicators among adults aged 18 years or older by using 2013 Behavioral Risk Factor Surveillance System (BRFSS) data; we applied their predicted probabilities to census population data to generate city-level, neighborhood-level, and zip-code–level estimates for the city of Boston, Massachusetts.

Results

By comparing the predicted estimates with their corresponding direct estimates from a locally administered survey (Boston BRFSS 2010 and 2013), we found that our model-based estimates for most of the selected health indicators at the city level were close to the direct estimates from the local survey. We also found strong correlation between the model-based estimates and direct survey estimates at neighborhood and zip code levels for most indicators.

Conclusion

Findings suggest that our model-based estimates are reliable and valid at the city level for certain health outcomes. Local health authorities can use the neighborhood-level estimates if high quality local health survey data are not otherwise available.

Reducing Disparities in Cancer Screening and Prevention through Community-Based Participatory Research Partnerships with Local Libraries: A Comprehensive Dynamic Trial

Reduction of cancer-related disparities requires strategies that link medically underserved communities to preventive care. In this community-based participatory research project, a public library system brought together stakeholders to plan and undertake programs to address cancer screening and risk behavior. This study was implemented over 48 months in 20 large urban neighborhoods, selected to reach diverse communities disconnected from care. In each neighborhood, Cancer Action Councils were organized to conduct a comprehensive dynamic trial, an iterative process of program planning, implementation and evaluation. This process was phased into neighborhoods in random, stepped-wedge sequence. Population-level outcomes included self-reported screening adherence and smoking cessation, based on street intercept interviews. Event-history regressions (n = 9374) demonstrated that adherence outcomes were associated with program implementation, as were mediators such as awareness of screening programs and cancer information seeking. Findings varied by ethnicity, and were strongest among respondents born outside the U.S. or least engaged in care. This intervention impacted health behavior in diverse, underserved and vulnerable neighborhoods. It has been sustained as a routine library system program for several years after conclusion of grant support. In sum, participatory research with the public library system offers a flexible, scalable approach to reduce cancer health disparities.

Integrating national surveys to estimate small area variations in poor health and limiting long-term illness in Great Britain

OBJECTIVES

This study aims to address, for the first time, the challenges of constructing small area estimates of health status using linked national surveys. The study also seeks to assess the concordance of these small area estimates with data from national censuses.

SETTING

Population level health status in England, Scotland and Wales.

PARTICIPANTS

A linked integrated dataset of 23 374 survey respondents (16+ years) from the 2011 waves of the Health Survey for England (n=8603), the Scottish Health Survey (n=7537) and the Welsh Health Survey (n=7234).

PRIMARY AND SECONDARY OUTCOME MEASURES

Population prevalence of poorer self-rated health and limiting long-term illness. A multilevel small area estimation modelling approach was used to estimate prevalence of these outcomes for middle super output areas in England and Wales and intermediate zones in Scotland. The estimates were then compared with matched measures from the contemporaneous 2011 UK Census.

RESULTS

There was a strong positive association between the small area estimates and matched census measures for all three countries for both poorer self-rated health (r=0.828, 95% CI 0.821 to 0.834) and limiting long-term illness (r=0.831, 95% CI 0.824 to 0.837), although systematic differences were evident, and small area estimation tended to indicate higher prevalences than census data.

CONCLUSIONS

Despite strong concordance, variations in the small area prevalences of poorer self-rated health and limiting long-term illness evident in census data cannot be replicated perfectly using small area estimation with linked national surveys. This reflects a lack of harmonisation between surveys over question wording and design. The nature of small area estimates as 'expected values' also needs to be better understood.

A geographic information system-based method for estimating cancer rates in non-census defined geographical areas

PURPOSE

To address locally relevant cancer-related health issues, health departments frequently need data beyond that contained in standard census area-based statistics. We describe a geographic information system-based method for calculating age-standardized cancer incidence rates in non-census defined geographical areas using publically available data.

METHODS

Aggregated records of cancer cases diagnosed from 2009 through 2013 in each of Chicago's 77 census-defined community areas were obtained from the Illinois State Cancer Registry. Areal interpolation through dasymetric mapping of census blocks was used to redistribute populations and case counts from community areas to Chicago's 50 politically defined aldermanic wards, and ward-level age-standardized 5-year cumulative incidence rates were calculated.

RESULTS

Potential errors in redistributing populations between geographies were limited to <1.5% of the total population, and agreement between our ward population estimates and those from a frequently cited reference set of estimates was high (Pearson correlation r = 0.99, mean difference = -4 persons). A map overlay of safety-net primary care clinic locations and ward-level incidence rates for advanced-staged cancers revealed potential pathways for prevention.

CONCLUSIONS

Areal interpolation through dasymetric mapping can estimate cancer rates in non-census defined geographies. This can address gaps in local cancer-related health data, inform health resource advocacy, and guide community-centered cancer prevention and control.

State and Local Chronic Disease Surveillance Using Electronic Health Record Systems

OBJECTIVES

To assess the feasibility of chronic disease surveillance using distributed analysis of electronic health records and to compare results with Behavioral Risk Factor Surveillance System (BRFSS) state and small-area estimates.

METHODS

We queried the electronic health records of 3 independent Massachusetts-based practice groups using a distributed analysis tool called MDPHnet to measure the prevalence of diabetes, asthma, smoking, hypertension, and obesity in adults for the state and 13 cities. We adjusted observed rates for age, gender, and race/ethnicity relative to census data and compared them with BRFSS state and small-area estimates.

RESULTS

The MDPHnet population under surveillance included 1 073 545 adults (21.8% of the state adult population). MDPHnet and BRFSS state-level estimates were similar: 9.4% versus 9.7% for diabetes, 10.0% versus 12.0% for asthma, 13.5% versus 14.7% for smoking, 26.3% versus 29.6% for hypertension, and 22.8% versus 23.8% for obesity. Correlation coefficients for MDPHnet versus BRFSS small-area estimates ranged from 0.890 for diabetes to 0.646 for obesity.

CONCLUSIONS

Chronic disease surveillance using electronic health record data is feasible and generates estimates comparable with BRFSS state and small-area estimates.

Advances in spatial epidemiology and geographic information systems

The field of spatial epidemiology has evolved rapidly in the past 2 decades. This study serves as a brief introduction to spatial epidemiology and the use of geographic information systems in applied research in epidemiology. We highlight technical developments and highlight opportunities to apply spatial analytic methods in epidemiologic research, focusing on methodologies involving geocoding, distance estimation, residential mobility, record linkage and data integration, spatial and spatio-temporal clustering, small area estimation, and Bayesian applications to disease mapping. The articles included in this issue incorporate many of these methods into their study designs and analytical frameworks. It is our hope that these studies will spur further development and utilization of spatial analysis and geographic information systems in epidemiologic research.

Geography of Adolescent Obesity in the U.S., 2007-2011

INTRODUCTION

Obesity remains a significant threat to the current and long-term health of U.S. adolescents. The authors developed county-level estimates of adolescent obesity for the contiguous U.S., and then explored the association between 23 conceptually derived area-based correlates of adolescent obesity and ecologic obesity prevalence.

METHODS

Multilevel small area regression methods applied to the 2007 and 2011-2012 National Survey of Children's Health produced county-level obesity prevalence estimates for children aged 10-17 years. Exploratory multivariable Bayesian regression estimated the cross-sectional association between nutrition, activity, and macrosocial characteristics of counties and states, and county-level obesity prevalence. All analyses were conducted in 2015.

RESULTS

Adolescent obesity varies geographically with clusters of high prevalence in the Deep South and Southern Appalachian regions. Geographic disparities and clustering in observed data are largely explained by hypothesized area-based variables. In adjusted models, activity environment, but not nutrition environment variables were associated with county-level obesity prevalence. County violent crime was associated with higher obesity, whereas recreational facility density was associated with lower obesity. Measures of the macrosocial and relational domain, including community SES, community health, and social marginalization, were the strongest correlates of county-level obesity.

CONCLUSIONS

County-level estimates of adolescent obesity demonstrate notable geographic disparities, which are largely explained by conceptually derived area-based contextual measures. This ecologic exploratory study highlights the importance of taking a multidimensional approach to understanding the social and community context in which adolescents make obesity-relevant behavioral choices.

Geographic Accessibility of Pulmonologists for Adults With COPD: United States, 2013

BACKGROUND

Geographic clusters in prevalence and hospitalizations for COPD have been identified at national, state, and county levels. The study objective is to identify county-level geographic accessibility to pulmonologists for adults with COPD.

METHODS

Service locations of 12,392 practicing pulmonologists and 248,160 primary care physicians were identified from the 2013 National Provider Identifier Registry and weighted by census block-level populations within a series of circular distance buffer zones. Model-based county-level population counts of US adults ≥ 18 years of age with COPD were estimated from the 2013 Behavioral Risk Factor Surveillance System. The percentages of all estimated adults with potential access to at least one provider type and the county-level ratio of adults with COPD per pulmonologist were estimated for selected distances.

RESULTS

Most US adults (100% in urbanized areas, 99.5% in urban clusters, and 91.7% in rural areas) had geographic access to a primary care physician within a 10-mile buffer distance; almost all (≥ 99.9%) had access to a primary care physician within 50 miles. At least one pulmonologist within 10 miles was available for 97.5% of US adults living in urbanized areas, but only for 38.3% in urban clusters and 34.5% in rural areas. When distance increased to 50 miles, at least one pulmonologist was available for 100% in urbanized areas, 93.2% in urban clusters, and 95.2% in rural areas. County-level ratios of adults with COPD per pulmonologist varied greatly across the United States, with residents in many counties in the Midwest having no pulmonologist within 50 miles.

CONCLUSIONS

County-level geographic variations in pulmonologist access for adults with COPD suggest that those adults with limited access will have to depend on care from primary care physicians.

Prevalence of Doctor-Diagnosed Arthritis at State and County Levels - United States, 2014

Doctor-diagnosed arthritis is a common chronic condition that affects approximately 52.5 million (22.7%) adults in the United States and is a leading cause of disability (1,2). The prevalence of doctor-diagnosed arthritis has been well documented at the national level (1), but little has been published at the state level and the county level, where interventions are carried out and can have their greatest effect. To estimate the prevalence of doctor-diagnosed arthritis among adults at the state and county levels, CDC analyzed data from the 2014 Behavioral Risk Factor Surveillance System (BRFSS). This report summarizes the results of that analysis, which found that, for all 50 states and the District of Columbia (DC) overall, the age-standardized median prevalence of doctor-diagnosed arthritis was 24% (range = 18.8%-35.5%). The age-standardized model-predicted prevalence of doctor-diagnosed arthritis varied substantially by county, with estimates ranging from 15.8% to 38.6%. The high prevalence of arthritis in all counties, and the high frequency of arthritis-attributable limitations (1) among adults with arthritis, suggests that states and counties might benefit from expanding underused, evidence-based interventions for arthritis that can reduce arthritis symptoms and improve self-management.