Michael Oakes

Compulsive Sexual Behavior and Risk for Unsafe Sex Among Internet Using Men Who Have Sex with Men

The present study explored the relationship between compulsive sexual behavior (CSB) and unprotected anal intercourse (UAI) for men who have sex with men (MSM) across a number of ethnic/racial groups and who used the Internet to seek sexual partners. A sample of 2,716 MSM (512 Asian, 445 Black, 683 Latino, 348 Other, 728 White) completed on online survey that collected information about their sexual behaviors with partners met online and offline. The survey also included the Compulsive Sexual Behavior Inventory (CSBI). Consistent with the notion that CSB is a stable trait, higher scores on the CSBI were associated with greater odds for engaging in UAI, regardless of the context in which sex partners were met (online or offline). Differences in median CSB scores were generally similar across racial and ethnic groups. The median CSB score was significantly higher for HIV-positive participants than for HIV-negative participants. HIV-prevention interventions are needed among MSM, but should take into account that some may be resistant to risk reduction strategies because of CSB.

Standards for Environmental Measurement Using GIS: Toward a Protocol for Protocols

BACKGROUND Interdisciplinary research regarding how the built environment influences physical activity has recently increased. Many research projects conducted jointly by public health and environmental design professionals are using geographic information systems (GIS) to objectively measure the built environment. Numerous methodological issues remain, however, and environmental measurements have not been well documented with accepted, common definitions of valid, reliable variables. METHODS This paper proposes how to create and document standardized definitions for measures of environmental variables using GIS with the ultimate goal of developing reliable, valid measures. Inherent problems with software and data that hamper environmental measurement can be offset by protocols combining clear conceptual bases with detailed measurement instructions. RESULTS Examples demonstrate how protocols can more clearly translate concepts into specific measurement. CONCLUSIONS This paper provides a model for developing protocols to allow high quality comparative research on relationships between the environment and physical activity and other outcomes of public health interest.

Efficacy of feeding plasma-derived commercial colostrum replacer for the prevention of transmission of Mycobacterium avium subsp paratuberculosis in Holstein calves.

OBJECTIVE To estimate the relative risk of paratuberculosis (Johnes disease [JD]) in calves fed a plasma-derived colostrum-replacement (CR) product versus raw bovine maternal colostrum (MC). STUDY DESIGN Randomized controlled clinical trial. ANIMALS 497 heifer calves born in 12 JD-endemic commercial Holstein dairy farms located in Minnesota and Wisconsin. PROCEDURES Every calf was separated from its dam within 30 to 60 minutes after birth and systematically assigned to be fed raw bovine MC (control group, n = 261 calves) or CR (treatment group, 236 calves). The calves were monitored to adulthood and tested for Mycobacterium avium subsp paratuberculosis (MAP) infection by use of an ELISA to detect serum antibodies against MAP and bacterial culture for MAP in feces at approximately 30, 42, and 54 months of age. Weibull regression models were used to evaluate the effect of feeding CR (vs raw bovine MC) on the risk of developing JD infection. RESULTS Calves fed CR at birth were less likely (hazard ratio = 0.559) to become infected with MAP (as determined by use of an ELISA, bacterial culture, or both diagnostic tests), compared with the likelihood for calves fed MC at birth. CONCLUSIONS AND CLINICAL RELEVANCE This study revealed that feeding CR reduced the risk of developing MAP infection in Holstein calves born in JD-endemic herds, which implied that feeding raw bovine MC may be a source of MAP for calves. Plasma colostrum-replacement products may be an effective management tool for use in dairy herds attempting to reduce the prevalence of JD.

The relationship between antenatal provider type and maternal care in rural Ghana: a cross-sectional study

To investigate the influence of antenatal provider type on maternity care in rural Ghana.

Pathological and Problem Gambling among Veterans in Clinical Care: Prevalence, Demography, and Clinical Correlates

BACKGROUND AND OBJECTIVES The aim of the study was to estimate prevalence rates of pathological gambling and problem gambling among veterans receiving VA care, since several studies have suggested that VA patients may be at increased risk to these conditions. SAMPLE consisted of 1,999 veterans randomly selected from VA centers and community clinics in the Albuquerque and Minneapolis catchment areas. Women and younger veterans were oversampled, due to anticipated low rates in these two groups. RESULTS revealed that the lifetime prevalence rate of pathological gambling weighted for current VA patients was 2.0%, twice the general adult population rate. Current 1-year weighted prevalence of pathological gambling was .9%, with an additional .2% having continued problem gambling and .9% recovered. Lifetime weighted problem gambling rate was 8.8%. Altogether, 10.7% had lifetime pathological gambling or problem gambling. Women had higher rates of pathological gambling, but similar rates of problem gambling compared to men. The greater prevalence of pathological gambling for younger veterans aged 20-29 (1.3%) compared to veterans aged 30-39 (.8%) was unusual and warrants further investigation. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE Veterans in VA care have higher rates of gambling problems than the general adult population. Female and young veterans have rates higher than those observed in other surveys of women and young adults.

Analytical Methods for a Learning Health System: 3. Analysis of Observational Studies

The third paper in a series on how learning health systems can use routinely collected electronic health data (EHD) to advance knowledge and support continuous learning, this review describes how analytical methods for individual-level electronic health data EHD, including regression approaches, interrupted time series (ITS) analyses, instrumental variables, and propensity score methods, can also be used to address the question of whether the intervention “works.” The two major potential sources of bias in non-experimental studies of health care interventions are that the treatment groups compared do not have the same probability of treatment or exposure and the potential for confounding by unmeasured covariates. Although very different, the approaches presented in this chapter are all based on assumptions about data, causal relationships, and biases. For instance, regression approaches assume that the relationship between the treatment, outcome, and other variables is properly specified, all of the variables are available for analysis (i.e., no unobserved confounders) and measured without error, and that the error term is independent and identically distributed. The instrumental variables approach requires identifying an instrument that is related to the assignment of treatment but otherwise has no direct on the outcome. Propensity score methods approaches, on the other hand, assume that there are no unobserved confounders. The epidemiological designs discussed also make assumptions, for instance that individuals can serve as their own control. To properly address these assumptions, analysts should conduct sensitivity analyses within the assumptions of each method to assess the potential impact of what cannot be observed. Researchers also should analyze the same data with different analytical approaches that make alternative assumptions, and to apply the same methods to different data sets. Finally, different analytical methods, each subject to different biases, should be used in combination and together with different designs, to limit the potential for bias in the final results.

Analytical Methods for a Learning Health System: 1. Framing the Research Question

Learning health systems use routinely collected electronic health data (EHD) to advance knowledge and support continuous learning. Even without randomization, observational studies can play a central role as the nation’s health care system embraces comparative effectiveness research and patient-centered outcomes research. However, neither the breadth, timeliness, volume of the available information, nor sophisticated analytics, allow analysts to confidently infer causal relationships from observational data. However, depending on the research question, careful study design and appropriate analytical methods can improve the utility of EHD. The introduction to a series of four papers, this review begins with a discussion of the kind of research questions that EHD can help address, noting how different evidence and assumptions are needed for each. We argue that when the question involves describing the current (and likely future) state of affairs, causal inference is not relevant, so randomized clinical trials (RCTs) are not necessary. When the question is whether an intervention improves outcomes of interest, causal inference is critical, but appropriately designed and analyzed observational studies can yield valid results that better balance internal and external validity than typical RCTs. When the question is one of translation and spread of innovations, a different set of questions comes into play: How and why does the intervention work? How can a model be amended or adapted to work in new settings? In these “delivery system science” settings, causal inference is not the main issue, so a range of quantitative, qualitative, and mixed research designs are needed. We then describe why RCTs are regarded as the gold standard for assessing cause and effect, how alternative approaches relying on observational data can be used to the same end, and how observational studies of EHD can be effective complements to RCTs. We also describe how RCTs can be a model for designing rigorous observational studies, building an evidence base through iterative studies that build upon each other (i.e., confirmation across multiple investigations).

Risk profiling of cattle farms as a potential tool in risk-based surveillance for Mycobacterium bovis infection among cattle in tuberculosis-free areas.

OBJECTIVE To develop a cattle herd risk-profiling system that could potentially inform risk-based surveillance strategies for Mycobacterium bovis infection in cattle and provide information that could be used to help direct resource allocation by a state agency for this purpose. DESIGN Cross-sectional study. SAMPLE Records for any size movement (importation) of cattle into Minnesota from other US states during 2009 (n = 7,185) and 2011 (8,107). PROCEDURES Data from certificates of veterinary inspection were entered into a spreadsheet. Movement data were summarized at premises and county levels, and for each level, the distribution of cattle moved and number of movements were evaluated. Risk profiling (assessment and categorization of risk for disease introduction) for each import movement was performed on the basis of known risk factors. Latent class analysis was used to assign movements to risk classifications with adjustment on the basis of expert opinions from personnel knowledgeable about bovine tuberculosis; these data were used to classify premises as very high, high, medium, or low risk for disease introduction. RESULTS In each year, approximately 1,500 premises imported cattle, typically beef and feeder types, with the peak of import movements during the fall season. The risk model identified 4 risk classes for cattle movements. Approximately 500 of the estimated 27,406 (2%) cattle premises in Minnesota were in the very high or high risk groups for either year; greatest density of these premises was in the southeast and southwest regions of the state. CONCLUSIONS AND CLINICAL RELEVANCE A risk-profiling approach was developed that can be applied in targeted surveillance efforts for bovine tuberculosis, particularly in disease-free areas.

Work Group III

Progress in transdisciplinary research addressing the health effects of the food and physical activity environments appears hampered by several methodologic obstacles, including: (1) the absence of clear, testable conceptual models; (2) slow adoption of practicable, rigorous research designs; (3) improper use of analytic techniques; and (4) concerns about ubiquitous measurement error. The consequence of such obstacles is that data collected as part of the typical study are more complex than need be. We offer diagnoses and recommendations from an NIH-sponsored meeting that addressed core issues in food- and physical activity-environment research. Recommendations include improved conceptual models and more elaborate theories, experimental thinking and increased attention to causal effect estimation, adoption of cross-validation techniques, use of existing measurement-error models, and increased support for methodologic research.