Race Disparities in the Use of Prevention, Screening, and Monitoring Services in Michigan Medicare Beneficiaries With Type 2 Diabetes and Combinations of Multiple Chronic Conditions.

People with diabetes need routine health care to prevent potential exacerbations of diabetes and detect or prevent the development of additional chronic conditions that can worsen the course of diabetes. Using 2012 Medicare claims data from the State of Michigan for 443,932 beneficiaries with type 2 diabetes, we determined that there are differences between white and racial/ethnic minority people with diabetes in accessing any preventive care and in the amount of service used once they do access care, even after adjusting for the presence of multiple chronic conditions.

General population estimates of the association between college experience and the odds of forced intercourse.

Sexual assault on college campuses is a pervasive problem, recently receiving increased scientific and policy attention. However, the high focus on college student experience ignores general population prevalence, trends, and differences between those with college experience and those without. We analyze measures from the National Survey of Family Growth (NSFG) to provide a general population view of experiences with forced intercourse. Forced intercourse is a common experience in the U.S. population, has remained stable in recent years, and varies greatly by gender, age and race. The odds of forced intercourse are also significantly higher among those with less than four years of college. This ubiquitous public health problem is not limited to college campuses. Measures from the NSFG are an important resource for understanding population rates of (and trends in) forced intercourse, providing information to guide interventions and better target scientific investigation.

Alternative Approaches to Assessing Nonresponse Bias in Longitudinal Survey Estimates: An Application to Substance-Use Outcomes Among Young Adults in the United States.

We evaluated alternative approaches to assessing and correcting for nonresponse bias in a longitudinal survey. We considered the changes in substance-use outcomes over a 3-year period among young adults aged 18-24 years (n = 5,199) in the United States, analyzing data from the National Epidemiologic Survey on Alcohol and Related Conditions. This survey collected a variety of substance-use information from a nationally representative sample of US adults in 2 waves: 2001-2002 and 2004-2005. We first considered nonresponse rates in the second wave as a function of key substance-use outcomes in wave 1. We then evaluated 5 alternative approaches designed to correct for nonresponse bias under different attrition mechanisms, including weighting adjustments, multiple imputation, selection models, and pattern-mixture models. Nonignorable attrition in a longitudinal survey can lead to bias in estimates of change in certain health behaviors over time, and only selected procedures enable analysts to assess the sensitivity of their inferences to different assumptions about the extent of nonignorability. We compared estimates based on these 5 approaches, and we suggest a road map for assessing the risk of nonresponse bias in longitudinal studies. We conclude with directions for future research in this area given the results of our evaluations.

"Clustering by interviewer": a source of variance that is unaccounted for in single-stage health surveys.

Although the impact of interviewers on survey measurement has been studied for more than 85 years, such impacts are rarely considered in the analysis of health surveys. This issue is particularly important with single-stage surveys such as that used in the Behavioral Risk Factor Surveillance System (BRFSS), where there are no sampling clusters in which interviewer effects could be captured. The BRFSS involves an ongoing telephone survey of the health behaviors of US adults and was established in 1984 by the Centers for Disease Control and Prevention. Public-use BRFSS data files are widely used by epidemiologists and public health researchers to describe the health behaviors of adults in the United States. Since its onset, the BRFSS has provided identification codes for telephone interviewers completing BRFSS interviews in its public-use data files; however, a review of BRFSS publications shows no evidence that these codes have been used in estimating standard errors. In this paper we analyze data from the 2012 BRFSS, illustrate both design-based and model-based approaches to incorporating interviewer effects in variance estimation, and find evidence of substantial interviewer effects for 5 key estimates across states. These results suggest that BRFSS analysts should consider accounting for interviewer effects, and we provide example code enabling analysts to do so. We conclude with suggestions regarding possible directions for future research.