Adam S. Vaughan

Understanding Racial HIV/STI Disparities in Black and White Men Who Have Sex with Men: A Multilevel Approach

Background The reasons for black/white disparities in HIV epidemics among men who have sex with men have puzzled researchers for decades. Understanding reasons for these disparities requires looking beyond individual-level behavioral risk to a more comprehensive framework. Methods and Findings From July 2010-Decemeber 2012, 803 men (454 black, 349 white) were recruited through venue-based and online sampling; consenting men were provided HIV and STI testing, completed a behavioral survey and a sex partner inventory, and provided place of residence for geocoding. HIV prevalence was higher among black (43%) versus white (13% MSM (prevalence ratio (PR) 3.3, 95% confidence interval (CI): 2.5–4.4). Among HIV-positive men, the median CD4 count was significantly lower for black (490 cells/µL) than white (577 cells/µL) MSM; there was no difference in the HIV RNA viral load by race. Black men were younger, more likely to be bisexual and unemployed, had less educational attainment, and reported fewer male sex partners, fewer unprotected anal sex partners, and less non-injection drug use. Black MSM were significantly more likely than white MSM to have rectal chlamydia and gonorrhea, were more likely to have racially concordant partnerships, more likely to have casual (one-time) partners, and less likely to discuss serostatus with partners. The census tracts where black MSM lived had higher rates of poverty and unemployment, and lower median income. They also had lower proportions of male-male households, lower male to female sex ratios, and lower HIV diagnosis rates. Conclusions Among black and white MSM in Atlanta, disparities in HIV and STI prevalence by race are comparable to those observed nationally. We identified differences between black and white MSM at the individual, dyadic/sexual network, and community levels. The reasons for black/white disparities in HIV prevalence in Atlanta are complex, and will likely require a multilevel framework to understand comprehensively.

Connecting Race and Place: A County-Level Analysis of White, Black, and Hispanic HIV Prevalence, Poverty, and Level of Urbanization

OBJECTIVES We evaluated the role of poverty in racial/ethnic disparities in HIV prevalence across levels of urbanization. METHODS Using national HIV surveillance data from the year 2009, we constructed negative binomial models, stratified by urbanization, with an outcome of race-specific, county-level HIV prevalence rates and covariates of race/ethnicity, poverty, and other publicly available data. We estimated model-based Black-White and Hispanic-White prevalence rate ratios (PRRs) across levels of urbanization and poverty. RESULTS We observed racial/ethnic disparities for all strata of urbanization across 1111 included counties. Poverty was associated with HIV prevalence only in major metropolitan counties. At the same level of urbanization, Black-White and Hispanic-White PRRs were not statistically different from 1.0 at high poverty rates (Black-White PRR = 1.0, 95% confidence interval [CI] = 0.4, 2.9; Hispanic-White PRR = 0.4, 95% CI = 0.1, 1.6). In nonurban counties, racial/ethnic disparities remained after we controlled for poverty. CONCLUSIONS The association between HIV prevalence and poverty varies by level of urbanization. HIV prevention interventions should be tailored to this understanding. Reducing racial/ethnic disparities will require multifactorial interventions linking social factors with sexual networks and individual risks.

Disparities in Temporal and Geographic Patterns of Declining Heart Disease Mortality by Race and Sex in the United States, 1973-2010.

Background Examining small‐area differences in the strength of declining heart disease mortality by race and sex provides important context for current racial and geographic disparities and identifies localities that could benefit from targeted interventions. We identified and described temporal trends in declining county‐level heart disease mortality by race, sex, and geography between 1973 and 2010. Methods and Results Using a Bayesian hierarchical model, we estimated age‐adjusted mortality with diseases of the heart listed as the underlying cause for 3099 counties. County‐level percentage declines were calculated by race and sex for 3 time periods (1973–1985, 1986–1997, 1998–2010). Strong declines were statistically faster or no different than the total national decline in that time period. We observed county‐level race–sex disparities in heart disease mortality trends. Continual (from 1973 to 2010) strong declines occurred in 73.2%, 44.6%, 15.5%, and 17.3% of counties for white men, white women, black men, and black women, respectively. Delayed (1998–2010) strong declines occurred in 15.4%, 42.0%, 75.5%, and 76.6% of counties for white men, white women, black men, and black women, respectively. Counties with the weakest patterns of decline were concentrated in the South. Conclusions Since 1973, heart disease mortality has declined substantially for these race–sex groups. Patterns of decline differed by race and geography, reflecting potential disparities in national and local drivers of these declines. Better understanding of racial and geographic disparities in the diffusion of heart disease prevention and treatment may allow us to find clues to progress toward racial and geographic equity in heart disease mortality.

Changes in the Geographic Patterns of Heart Disease Mortality in the United States 1973 to 2010

Background— Although many studies have documented the dramatic declines in heart disease mortality in the United States at the national level, little attention has been given to the temporal changes in the geographic patterns of heart disease mortality. Methods and Results— Age-adjusted and spatially smoothed county-level heart disease death rates were calculated for 2-year intervals from 1973 to 1974 to 2009 to 2010 for those aged ≥35 years. Heart disease deaths were defined according to the International Classification of Diseases codes for diseases of the heart in the eighth, ninth, and tenth revisions of the International Classification of Diseases. A fully Bayesian spatiotemporal model was used to produce precise rate estimates, even in counties with small populations. A substantial shift in the concentration of high-rate counties from the Northeast to the Deep South was observed, along with a concentration of slow-decline counties in the South and a nearly 2-fold increase in the geographic inequality among counties. Conclusions— The dramatic change in the geographic patterns of heart disease mortality during 40 years highlights the importance of small-area surveillance to reveal patterns that are hidden at the national level, gives communities the historical context for understanding their current burden of heart disease, and provides important clues for understanding the determinants of the geographic disparities in heart disease mortality.

Vital Signs: Recent Trends in Stroke Death Rates - United States, 2000-2015

Introduction The prominent decline in U.S. stroke death rates observed for more than 4 decades has slowed in recent years. CDC examined trends and patterns in recent stroke death rates among U.S. adults aged ≥35 years by age, sex, race/ethnicity, state, and census region. Methods Trends in the rates of stroke as the underlying cause of death during 2000–2015 were analyzed using data from the National Vital Statistics System. Joinpoint software was used to identify trends in stroke death rates, and the excess number of stroke deaths resulting from unfavorable changes in trends was estimated. Results Among adults aged ≥35 years, age-standardized stroke death rates declined 38%, from 118.4 per 100,000 persons in 2000 to 73.3 per 100,000 persons in 2015. The annual percent change (APC) in stroke death rates changed from 2000 to 2015, from a 3.4% decrease per year during 2000–2003, to a 6.6% decrease per year during 2003–2006, a 3.1% decrease per year during 2006–2013, and a 2.5% (nonsignificant) increase per year during 2013–2015. The last trend segment indicated a reversal from a decrease to a statistically significant increase among Hispanics (APC = 5.8%) and among persons in the South Census Region (APC = 4.2%). Declines in stroke death rates failed to continue in 38 states, and during 2013–2015, an estimated 32,593 excess stroke deaths might not have occurred if the previous rate of decline could have been sustained. Conclusions and Implications for Public Health Practice Prior declines in stroke death rates have not continued in recent years, and substantial variations exist in timing and magnitude of change by demographic and geographic characteristics. These findings suggest the importance of strategically identifying opportunities for prevention and intervening in vulnerable populations, especially because effective and underused interventions to prevent stroke incidence and death are known to exist.

Use of a Google Map Tool Embedded in an Internet Survey Instrument: Is it a Valid and Reliable Alternative to Geocoded Address Data?

Background Men who have sex with men (MSM) in the United States are at high risk for human immunodeficiency virus (HIV) and poor HIV related outcomes. Maps can be used to identify, quantify, and address gaps in access to HIV care among HIV-positive MSM, and tailor intervention programs based on the needs of patients being served. Objective The objective of our study was to assess the usability of a Google map question embedded in a Web-based survey among Atlanta-based, HIV-positive MSM, and determine whether it is a valid and reliable alternative to collection of address-based data on residence and last HIV care provider. Methods Atlanta-based HIV-positive MSM were recruited through Facebook and from two ongoing studies recruiting primarily through venue-based sampling or peer referral (VBPR). Participants were asked to identify the locations of their residence and last attended HIV care provider using two methods: (1) by entering the street address (gold standard), and (2) “clicking” on the locations using an embedded Google map. Home and provider addresses were geocoded, mapped, and compared with home and provider locations from clicked map points to assess validity. Provider location error values were plotted against home location error values, and a kappa statistic was computed to assess agreement in degree of error in identifying residential location versus provider location. Results The median home location error across all participants was 0.65 miles (interquartile range, IQR, 0.10, 2.5 miles), and was lower among Facebook participants (P<.001), whites (P<.001), and those reporting higher annual household income (P=.04). Median home location error was lower, although not statistically significantly, among older men (P=.08) and those with higher educational attainment (P=.05). The median provider location error was 0.32 miles (IQR, 0.12, 1.2 miles), and did not vary significantly by age, recruitment method, race, income, or level of educational attainment. Overall, the kappa was 0.20, indicating poor agreement between the two error measures. However, those recruited through Facebook had a greater level of agreement (κ=0.30) than those recruited through VBPR methods (κ=0.16), demonstrating a greater level of consistency in using the map question to identify home and provider locations for Facebook-recruited individuals. Conclusions Most participants were able to click within 1 mile of their home address and their provider’s office, and were not always able to identify the locations on a map consistently, although some differences were observed across recruitment methods. This map tool may serve as the basis of a valid and reliable tool to identify residence and HIV provider location in the absence of geocoded address data. Further work is needed to improve and compare map tool usability with the results from this study.

Comparing methods of measuring geographic patterns in temporal trends: an application to county-level heart disease mortality in the United States, 1973 to 2010

PURPOSE To demonstrate the implications of choosing analytical methods for quantifying spatiotemporal trends, we compare the assumptions, implementation, and outcomes of popular methods using county-level heart disease mortality in the United States between 1973 and 2010. METHODS We applied four regression-based approaches (joinpoint regression, both aspatial and spatial generalized linear mixed models, and Bayesian space-time model) and compared resulting inferences for geographic patterns of local estimates of annual percent change and associated uncertainty. RESULTS The average local percent change in heart disease mortality from each method was -4.5%, with the Bayesian model having the smallest range of values. The associated uncertainty in percent change differed markedly across the methods, with the Bayesian space-time model producing the narrowest range of variance (0.0-0.8). The geographic pattern of percent change was consistent across methods with smaller declines in the South Central United States and larger declines in the Northeast and Midwest. However, the geographic patterns of uncertainty differed markedly between methods. CONCLUSIONS The similarity of results, including geographic patterns, for magnitude of percent change across these methods validates the underlying spatial pattern of declines in heart disease mortality. However, marked differences in degree of uncertainty indicate that Bayesian modeling offers substantially more precise estimates.

An application of propensity score weighting to quantify the causal effect of rectal sexually transmitted infections on incident HIV among men who have sex with men

BackgroundExploring causal associations in HIV research requires careful consideration of numerous epidemiologic limitations. First, a primary cause of HIV, unprotected anal intercourse (UAI), is time-varying and, if it is also associated with an exposure of interest, may be on a confounding path. Second, HIV is a rare outcome, even in high-risk populations. Finally, for most causal, non-preventive exposures, a randomized trial is impossible. In order to address these limitations and provide a practical illustration of efficient statistical control via propensity-score weighting, we examine the causal association between rectal STI and HIV acquisition in the InvolveMENt study, a cohort of Atlanta-area men who have sex with men (MSM). We hypothesized that, after controlling for potentially confounding behavioral and demographic factors, the significant STI-HIV association would attenuate, but yield an estimate of the causal effect.MethodsThe exposure of interest was incident rectal gonorrhea or chlamydia infection; the outcome was incident HIV infection. To adjust for behavioral confounding, while accounting for limited HIV infections, we used an inverse probability of treatment weighted (IPTW) Cox proportional hazards (PH) model for incident HIV. Weights were derived from propensity score modeling of the probability of incident rectal STI as a function of potential confounders, including UAI in the interval of rectal STI acquisition/censoring.ResultsOf 556 HIV-negative MSM at baseline, 552 (99%) men were included in this analysis. 79 men were diagnosed with an incident rectal STI and 26 with HIV. 6 HIV-infected men were previously diagnosed with a rectal STI. In unadjusted analysis, incident rectal STI was significantly associated with subsequent incident HIV (HR (95%CI): 3.6 (1.4-9.2)). In the final weighted and adjusted model, the association was attenuated and more precise (HR (95% CI): 2.7 (1.2-6.4)).ConclusionsWe found that, controlling for time-varying risk behaviors and time-invariant demographic factors, diagnosis with HIV was significantly associated with prior diagnosis of rectal CT or GC. Our analysis lends support to the causal effect of incident rectal STI on HIV diagnosis and provides a framework for similar analyses of HIV incidence.

Geographic Disparities in Declining Rates of Heart Disease Mortality in the Southern United States, 1973–2010

This map shows model-based, county-level percentage decline in heart disease death rates from 1973 to 2010 in the Southern United States. During this 37-year period, the fastest declines (in yellow) occurred primarily on the East Coast and central and west Texas, and the slowest declines (in dark blue) were concentrated largely in the counties along the Mississippi River and parts of Kentucky, Oklahoma, and Alabama, which are also areas characterized by extremely high spatially concentrated poverty rates (6).

Activity spaces of men who have sex with men: An initial exploration of geographic variation in locations of routine, potential sexual risk, and prevention behaviors

Theory and research on HIV and among men who have sex with men (MSM) have long suggested the importance of non-residential locations in defining structural exposures. Despite this, most studies within these fields define place as a residential context, neglecting the potential influence of non-residential locations on HIV-related outcomes. The concept of activity spaces, defined as a set of locations to which an individual is routinely exposed, represents one theoretical basis for addressing this potential imbalance. Using a one-time online survey to collect demographic, behavioral, and spatial data from MSM, this paper describes activity spaces and examines correlates of this spatial variation. We used latent class analysis to identify categories of activity spaces using spatial data on home, routine, potential sexual risk, and HIV prevention locations. We then assessed individual and area-level covariates for their associations with these categories. Classes were distinguished by the degree of spatial variation in routine and prevention behaviors (which were the same within each class) and in sexual risk behaviors (i.e., sex locations and locations of meeting sex partners). Partner type (e.g. casual or main) represented a key correlate of the activity space. In this early examination of activity spaces in an online sample of MSM, patterns of spatial behavior represent further evidence of significant spatial variation in locations of routine, potential HIV sexual risk, and HIV prevention behaviors among MSM. Although prevention behaviors tend to have similar geographic variation as routine behaviors, locations where men engage in potentially high-risk behaviors may be more spatially focused for some MSM than for others.