Blacks Smoke Less (and More) than Whites: Simpson’s Paradox in U.S. Smoking Rates, 2008 to 2012

Racial disparities in health and health behaviors among gay, lesbian, bisexual and heterosexual men and women in the BRFSS-SOP

Objectives: Research on sexual minority health lack examinations of how sexual orientation intersects with other identities, including racial/ethnic identity, to shape health outcomes among U.S. adults. This study examines how health status and health behavior varies for gay, lesbian, and bisexual men and women who identify as non-Hispanic white, non-Hispanic black, Latino, Asian/Pacific Islander, and American Indian/Alaskan Native. By examining health and health behaviors within and across sexual minority subgroups, our study reports on race/ethnic, gender, and sexual orientation specific health risks.Methods: We respond to shortcomings in current data by utilizing aggregated data from fourteen states from the Behavioral Risk Factor Surveillance System (BRFSS) collected between 2005 and 2010 (n = 557,773). We investigated the odds of reporting poorer health, current cigarette smoking, and obesity by sexual orientation within race/ethnic and gender subgroups; all statistical analyses were performed in 2016.Results: Results suggest persistent health and behavior disadvantages for lesbian and bisexual women of all racial and ethnic identities, relative to heterosexuals. Some of the heightened odds are extreme. Asian/Pacific Islander lesbian (OR = 3.92) and bisexual (OR = 4.61) women, for example, have 4.0 times higher odds of smoking than heterosexual A/PI women. Results for men are more variable. To illustrate, the odds of obesity for White and A/PI men are indistinguishable between bisexuals and heterosexuals, and Black and American Indian/Alaskan Native bisexuals have lower odds of obesity than their heterosexual counterparts.Conclusion: These findings highlight the need for policy efforts aimed at improving health and health behaviors among lesbian and bisexual women across groups, and more targeted efforts among sexual minority men.

Changing Trends of Atherosclerotic Risk Factors Among Patients With Acute Myocardial Infarction and Acute Ischemic Stroke

We aimed to evaluate the secular trends in demographics, risk factors, and clinical characteristics of patients presenting with acute myocardial infarction (AMI) or acute ischemic stroke (AIS), using a large nationally representative data set of in-hospital admissions. We used the 2003 to 2013 Nationwide Inpatient Sample. All admissions with primary diagnosis of AMI or AIS were included. Across 2003 to 2013, a total of 1,360,660 patients with AMI and 937,425 patients with AIS were included in the study. We noted a progressive reduction in the mean age of patients presenting with AMI and AIS (p trend <0.001 for all groups), implying that the burden of young patients with these acute syndromes is progressively increasing. In addition, there was a progressive increase in the proportion of patients who are uninsured among patients presenting with AMI and AIS. Furthermore, despite a progressively younger age at presentation, there was an observed increase in the prevalence of atherosclerotic risk factors including hypertension, hyperlipidemia, diabetes, smoking, and obesity among patients presenting with AMI or AIS during 2003 to 2013. Significant disparities were noted in the prevalence of risk factors among various demographic and geographical cohorts. Low socioeconomic status as well as uninsured patients had a significantly higher prevalence of preventable risk factors like smoking and obesity as compared to the high socioeconomic status and insured patients, respectively. In conclusion, there have been significant changes in the risk factor profile of patients presenting with AMI and AIS over the last decade.

Statistics, Adjusted Statistics, and Maladjusted Statistics

Statistical adjustment is a ubiquitous practice in all quantitative fields that is meant to correct for improprieties or limitations in observed data, to remove the influence of nuisance variables or to turn observed correlations into causal inferences. These adjustments proceed by reporting not what was observed in the real world, but instead modeling what would have been observed in an imaginary world in which specific nuisances and improprieties are absent. These techniques are powerful and useful inferential tools, but their application can be hazardous or deleterious if consumers of the adjusted results mistake the imaginary world of models for the real world of data. Adjustments require decisions about which factors are of primary interest and which are imagined away, and yet many adjusted results are presented without any explanation or justification for these decisions. Adjustments can be harmful if poorly motivated, and are frequently misinterpreted in the media's reporting of scientific studies. Adjustment procedures have become so routinized that many scientists and readers lose the habit of relating the reported findings back to the real world in which we live.

Understanding Tobacco Use Behaviors Among African Americans: Progress, Critical Gaps, and Opportunities

INTRODUCTION

Although multiple factors likely influence the differences between African Americans (AAs) and whites in cardiovascular disease and lung cancer mortality rates, historical patterns of tobacco use, particularly cigarette smoking, are the major contributors. This issue of Nicotine & Tobacco Research presents original research, a review, and commentaries that will serve to advance our understanding of several relevant behavioral similarities and differences between AAs and whites.

BEHAVIORAL ANALYSIS

Here, we illustrate how the diverging trends in cigarette smoking between AA and white high school seniors observed since the mid-1970s were influenced by patterns of ever use and current use among ever users. During 1977 to 2014, the percentage of current users among ever users was higher, but less variable, among whites than AAs. Among adults, trends in self-reported cigarette smoking among non-Hispanic AAs and non-Hispanic whites are available since 1978. The trends observed were likely due in part to the maturation of the high school senior cohorts from the 1970s and 1980s when AA smoking rates declined sharply relative to whites. Later age of initiation among AAs and less quitting among older AAs, relative to whites, also contribute.

CONCLUSIONS

Further research on multiple topics, including the continuation of use among ever users, use of multiple combusted and noncombusted products, provision of cessation support services, influence of discrimination, and validity of self-report would expand the science base. Strategies to reduce the marketing and availability of menthol and other characterizing flavorings and to enrich environments would promote the public's health.

Improving Prognostic Web Calculators: Violation of Preferential Risk Independence

BACKGROUND

Web-based applications are available for prognostication of individual patients. These prognostic models were developed for groups of patients. No one is the average patient, and using these calculators to inform individual patients could provide misleading results.

OBJECTIVE

This article gives an example of paradoxical results that may emerge when indices used for prognosis of the average person are used for care of an individual patient.

METHODS

We calculated the expected mortality risks of stomach cancer and its associated comorbidities. Mortality risks were calculated using data from 140,699 Veterans Administration nursing home residents.

RESULTS

On average, a patient with hypertension has a higher risk of mortality than one without hypertension. Surprisingly, among patients with lung cancer, hypertension is protective and reduces risk of mortality. This paradoxical result is explained by how group-level, average prognosis could mislead individual patients. In particular, average prognosis of lung cancer patients reflects the impact of various comorbidities that co-occur in lung cancer patients. The presence of hypertension, a relatively mild comorbidity of lung cancer, indicates that more serious comorbidities have not occurred. It is not that hypertension is protective; it is the absence of more serious comorbidities that is protective. The article shows how the presence of these anomalies can be checked through the mathematical concept of preferential risk independence.

CONCLUSION

Instead of reporting average risk scores, web-based calculators may improve accuracy of predictions by reporting the unconfounded risks.