A new source of data for public health surveillance: Facebook likes.

BACKGROUND: Investigation into personal health has become focused on conditions at an increasingly local level, while response rates have declined and complicated the process of collecting data at an individual level. Simultaneously, social media data have exploded in availability and have been shown to correlate with the prevalence of certain health conditions. OBJECTIVE: Facebook likes may be a source of digital data that can complement traditional public health surveillance systems and provide data at a local level. We explored the use of Facebook likes as potential predictors of health outcomes and their behavioral determinants. METHODS: We performed principal components and regression analyses to examine the predictive qualities of Facebook likes with regard to mortality, diseases, and lifestyle behaviors in 214 counties across the United States and 61 of 67 counties in Florida. These results were compared with those obtainable from a demographic model. Health data were obtained from both the 2010 and 2011 Behavioral Risk Factor Surveillance System (BRFSS) and mortality data were obtained from the National Vital Statistics System. RESULTS: Facebook likes added significant value in predicting most examined health outcomes and behaviors even when controlling for age, race, and socioeconomic status, with model fit improvements (adjusted R(2)) of an average of 58% across models for 13 different health-related metrics over basic sociodemographic models. Small area data were not available in sufficient abundance to test the accuracy of the model in estimating health conditions in less populated markets, but initial analysis using data from Florida showed a strong model fit for obesity data (adjusted R(2)=.77). CONCLUSIONS: Facebook likes provide estimates for examined health outcomes and health behaviors that are comparable to those obtained from the BRFSS. Online sources may provide more reliable, timely, and cost-effective county-level data than that obtainable from traditional public health surveillance systems as well as serve as an adjunct to those systems.

A bibliometric analysis of U.S.-based research on the Behavioral Risk Factor Surveillance System.

BACKGROUND: Since Alan Pritchard defined bibliometrics as "the application of statistical methods to media of communication" in 1969, bibliometric analyses have become widespread. To date, however, bibliometrics has not been used to analyze publications related to the U.S. Behavioral Risk Factor Surveillance System (BRFSS). PURPOSE: To determine the most frequently cited BRFSS-related topical areas, institutions, and journals. METHODS: A search of the Web of Knowledge database in 2013 identified U.S.-published studies related to BRFSS, from its start in 1984 through 2012. Search terms were BRFSS, Behavioral Risk Factor Surveillance System, or Behavioral Risk Survey. The resulting 1,387 articles were analyzed descriptively and produced data for VOSviewer, a computer program that plotted a relevance distance-based map and clustered keywords from text in titles and abstracts. RESULTS: Topics, journals, and publishing institutions ranged widely. Most research was clustered by content area, such as cancer screening, access to care, heart health, and quality of life. The American Journal of Preventive Medicine and American Journal of Public Health published the most BRFSS-related papers (95 and 70, respectively). CONCLUSIONS: Bibliometrics can help identify the most frequently published BRFSS-related topics, publishing journals, and publishing institutions. BRFSS data are widely used, particularly by CDC and academic institutions such as the University of Washington and other universities hosting top-ranked schools of public health. Bibliometric analysis and mapping provides an innovative way of quantifying and visualizing the plethora of research conducted using BRFSS data and summarizing the contribution of this surveillance system to public health.

Obesity prevention: the impact of local health departments.

OBJECTIVE: To examine the association between bodyweight status and provision of population-based prevention services. DATA SOURCES: The National Association of City and County Health Officials 2005 Profile survey data, linked with two cross-sections of the Behavioral Risk Factor Surveillance System (BRFSS) survey in 2004 and 2005. STUDY DESIGN: Multilevel logistic regressions were used to examine the association between provision of obesity-prevention services and the change in risk of being obese or morbidly obese among BRFSS respondents. The estimation sample was stratified by sex. Low-income samples were also examined. Falsification tests were used to determine whether there is counterevidence. PRINCIPAL FINDINGS: Provision of population-based obesity-prevention services within the jurisdiction of local health departments and specifically those provided by the local health departments are associated with reduced risks of obesity and morbid obesity from 2004 to 2005. The magnitude of the association appears to be stronger among low-income populations and among women. Results of the falsification tests provide additional support of the main findings. CONCLUSIONS: Population-based obesity-prevention services may be useful in containing the obesity epidemic.

The role of geographic scale in testing the income inequality hypothesis as an explanation of health disparities.

This study re-examined the role of geographic scale in measuring income inequality and testing the income inequality hypothesis (IIH) as an explanation of health disparities. We merged Behavioral Risk Factor Surveillance System (BRFSS) 2000 data with income inequality indices constructed at different geographic scales to test the association between income inequality and four different health indicators, i.e., self-assessed health status as a morbidity measure, vaccination against influenza as a measure of use of preventive healthcare, having any kind of health insurance as a measure of access, and obesity as a modifiable health risk factor measure. Multilevel models are used in our regression of the health indicators on measures of income inequalities and control variables. Our analysis suggests that because income inequality is a contextual variable, income inequalities measured at different geographic scales have different interpretations and relate to societal characteristics at different levels. Therefore, a rejection of the IIH at one level does not necessarily negate the possibility that income inequality affects health at another level. Assessment across a variety of scales is needed to have a comprehensive picture of the IIH in any given study. Empirical results also show that whether the IIH holds could depend on the sex group examined and the health indicator used, which implies different mechanisms of IIH exist for different sex groups and health indicators, in addition to the geographic scale. The role of geographic scale should be more rigorously considered in social determinants of health research.

Evaluation of variance estimators for the concentration and health achievement indices: a Monte Carlo simulation.

Although the concentration index (CI) and the health achievement index (HAI) have been extensively used, previous studies have relied on bootstrapping to compute the variance of the HAI, whereas competing variance estimators exist for the CI. This paper provides methods of statistical inference for the HAI and compares the available variance estimators for both the CI and the HAI using Monte Carlo simulation. Results for both the CI and the HAI suggest that analytical methods and bootstrapping are well behaved. The convenient regression method gives standard errors close to the other methods, provided the CI is not too large (< 0.2), but otherwise tends to understate the standard errors. In our simulation setting, the improvement from the Newey-West correction over the convenient regression method has mixed evidence when the CI ≤ 0.1 and is modest when the CI > 0.1. Published 2011. This article is a US Government work and is in the public domain in the USA.

Examining the role of gender in career advancement at the Centers for Disease Control and Prevention.

During the past decade, efforts to promote gender parity in the healing and public health professions have met with only partial success. We provide a critical update regarding the status of women in the public health profession by exploring gender-related differences in promotion rates at the nation's leading public health agency, the Centers for Disease Control and Prevention (CDC). Using personnel data drawn from CDC, we found that the gender gap in promotion has diminished across time and that this reduction can be attributed to changes in individual characteristics (e.g., higher educational levels and more federal work experience). However, a substantial gap in promotion that cannot be explained by such characteristics has persisted, indicating continuing barriers in women's career advancement.