Objective and subjective poor mental health indicators among Arab Americans in Michigan: a population-based study.

Background: Arab Americans are at high risk for poor mental health outcomes and are difficult to study at a population level due to a lack of racial/ethnic identifiers for this population.Methods: Using data from the standalone 2013 Michigan Arab Behavioral Risk Factor Survey (MI ABRFS) we aimed to understand whether the burden of mental health differed between Arab Americans and non-Arab, non-Hispanic Whites. Two measures of mental health were used: a subjective (number of poor mental health days experienced in the past 30 days) and an objective (being diagnosed with depression) measure. Additionally, we aimed to understand the sociodemographic, stress, and health-related variables associated with the objective and subjective measures of psychopathologies in the Arab American population in Michigan using population-weighted logistic regression models with survey design correction.Results: Arab Americans had increased odds of adverse mental health when compared to non-Arab, non-Hispanic Whites for the subjective measure of number of poor mental health days (OR: 1.62, 95% CI: 1.08, 2.41) and decreased odds of reporting the objective measure of diagnosed depression (OR: 0.54, 95% CI: 0.30, 0.98). Having more than one poor mental health day and being diagnosed with depression among Arab Americans was associated with being female, unmarried, unemployed, and having experienced abuse as a child.Discussion: Combining mental health screenings with primary care check-ups among Arab Americans may be an important step in identifying individuals with mental health needs and extending access to care.

County Jail Incarceration Rates and County Mortality Rates in the United States, 1987-2016.

Objectives. To evaluate the relationship between changes in county jail incarceration rates and subsequent county mortality rates across the United States.Methods. We analyzed county jail incarceration rates from the Bureau of Justice Statistics from 1987 to 2016 for 1884 counties and mortality rates from the National Vital Statistics System. We fit 1-year-lagged quasi-Poisson 2-way fixed-effects models, controlling for unmeasured stable county characteristics, and measured time-varying confounders, including county poverty and crime rates.Results. A within-county increase in jail incarceration rates from the first to second quartile was associated with a 2.5% increase in mortality rates, adjusting for confounders (risk ratio [RR] = 1.03; 95% confidence interval [CI] = 1.02, 1.03). This association followed a dose-response relationship and was stronger for mortality among those aged 15 to 34 years (RR = 1.07; 95% CI = 1.06, 1.09).Conclusions. Within-county increases in jail incarceration rates are associated with increases in subsequent mortality rates after adjusting for important confounders.Public Health Implications. Our findings add to the growing body of empirical evidence of the harms of mass incarceration. The criminal justice reform and decarceration movements can use these findings as they develop strategies to end mass incarceration.

Relevance of the "Immigrant Health Paradox" for the Health of Arab Americans in California.

Objectives. To assess the validity of the immigrant health paradox among Arab Americans in California.Methods. We used data from the 2003 to 2017 California Health Interview Survey (n = 1425). We used survey-weighted χ2 and logistic regression analyses to compare Arabs by immigrant generation on socioeconomic indicators, health behaviors, and health outcomes.Results. Second-generation Arab Americans had higher odds of binge drinking (adjusted odds ratio [AOR] = 3.26; 95% confidence interval [CI] = 1.53, 6.94) in the past year than did first-generation Arab Americans. Third-generation Arab Americans had greater odds of receiving the influenza vaccine in the past year (AOR = 3.29; 95% CI = 1.09, 9.98) than did second-generation Arab Americans. Third-generation Arab Americans had increased odds of being overweight or obese when compared with first- (AOR = 2.59; 95% CI = 1.02, 6.58) and second-generation Arab Americans (AOR = 3.22; 95% CI = 1.25, 8.29), respectively.Conclusions. Alcohol use increased across immigrant generations, and we observed no differences in health outcomes, other than obesity. The immigrant health paradox does not appear to apply to Arab Americans in California; mechanisms that generate health in this population should be studied further.

Differences in health behaviors and health outcomes among non-Hispanic Whites and Arab Americans in a population-based survey in California.

BACKGROUND: Few population-based studies of Arab American health behaviors and outcomes exist outside of Michigan. We aimed to provide prevalence estimates of health behaviors and outcomes for Arab Americans and compare them to non-Hispanic Whites in California. METHODS: We used data from the 2003-2016 California Health Interview Surveys. We determined Arab American ethnicity using an algorithm that considered place of birth of the respondent or parent and use of Arabic language at home. Survey-weighted frequencies, chi-squared statistics, and logistic regression analyses were used to compare Arab Americans and non-Hispanic Whites on socioeconomic indicators, health behaviors and health outcomes. Multivariable models were adjusted for age, education level, and insurance status. RESULTS: Arab Americans had higher prevalence of no insurance, living below the federal poverty level, and home ownership than non-Hispanic Whites despite high levels of education and low unemployment prevalence. Arab Americans had reduced odds of alcohol consumption (OR: 0.33, 95% CI: 0.24, 0.45), binge drinking (OR: 0.28, 95% CI: 0.19, 0.40), and suicidal ideation (OR: 0.41, 0.25, 0.66) when compared to non-Hispanic Whites in multivariable models. Arab Americans had decreased odds of hypertension (OR: 0.64, 95% CI: 0.50, 0.83) and increased odds of diabetes (OR: 2.03, 95% CI: 1.23, 3.34) when compared to non-Hispanic Whites in multivariable models. CONCLUSIONS: Arab Americans in California participate in less risky health behaviors and have better health outcomes than non-Hispanic Whites, except with regards to diabetes. Future work aiming to understand the health of Arab Americans should allow for self-identification and less reliance on country of origin and language use at home for sample selection.

Web-Based Antismoking Advertising to Promote Smoking Cessation: A Randomized Controlled Trial.

BACKGROUND: Although hundreds of millions of dollars are spent each year on public health advertising, the advertisement content, design, and placement are usually developed by intuition rather than research. OBJECTIVE: The objective of our study was to develop a methodology for testing Web-based advertisements to promote smoking cessation. METHODS: We developed 10 advertisements that varied by their content (those that empower viewers to quit, help viewers to quit, or discuss the effects of smoking). We then conducted a series of Web-based randomized controlled trials that explored the effects of exposing users of Microsoft's Bing search engine to antismoking advertisements that differed by content, placement, or other characteristics. Finally, we followed users to explore whether they conducted subsequent searches for smoking cessation products or services. RESULTS: The advertisements were shown 710,106 times and clicked on 1167 times. In general, empowering advertisements had the greatest impact (hazard ratio [HR] 2.6, standard error [SE] 0.09 relative to nonempowering advertisements), but we observed significant variations by gender. For instance, we found that men exposed to smoking cessation advertisements were less likely than women to subsequently conduct smoking cessation searches (HR 0.2, SE 0.07), but that this likelihood increased 3.5 times in men exposed to advertisements containing empowering content. Women were more influenced by advertisements that emphasized the health effects of smoking. We also found that appearing at the top right of the page (HR 2.1, SE 0.07) or at the bottom rather than the top of a list (HR 1.1, SE 0.02) can improve smoking cessation advertisements' effectiveness in prompting future searches related to smoking cessation. CONCLUSIONS: Advertising should be targeted to different demographic groups in ways that are not always intuitive. Our study provides a method for testing the effectiveness of Web-based antismoking advertisements and demonstrates the importance of advertisements that are tailored according to specific demographics.

Commentary: Epidemiology in the era of big data.

Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called "three V's": variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field's future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future.

Calorie Offsets: Environmental Policy for the Food Environment.

Although obesity continues to challenge the public's health, effective policy solutions are wanting. Borrowing from environmental protection efforts, we explored the potential for a "calorie offset" regulatory mechanism, which is similar to the carbon emission offsets used to curb greenhouse gas emissions, to mitigate the harmful health externalities of unhealthy food production. This approach might have a number of advantages over traditional policy tools, and warrants attention from health policymakers and industry alike.

Evaluation of the charges, safety, and mortality of percutaneous renal thermal ablation using the nationwide inpatient sample.

PURPOSE: To perform a national analysis of safety, charges, complications, and mortality of percutaneous image-guided renal thermal ablation and compare outcomes by hospital volume. MATERIALS AND METHODS: Using the Nationwide Inpatient Sample, trends in the proportion of inpatient percutaneous renal thermal ablation procedures performed at high-volume centers in the United States from 2007-2011 were evaluated. In-hospital mortality, discharge to long-term care facility, length of stay, hospitalization charges, and postoperative complications were compared between high-volume and low-volume ablation centers. High volume was set at the 90th percentile for renal thermal ablation volume, which equated to seven or more patients per year. A multivariate logistic regression analysis adjusting for hospital volume, age, sex, Charlson Comorbidity Index, obesity, race, and insurance status was performed to analyze the influence of hospital volume on the above-listed outcomes. RESULTS: This study included 874 patients. The number of hospitals ranged from 59-77 depending on year. Overall, 328 patients (37.5%) were treated at high-volume ablation centers. The proportion of patients treated at high-volume centers decreased from 42.0% in 2007-2009 to 28.5% in 2010-2011. High-volume hospitals also performed significantly more partial nephrectomies than low-volume hospitals. On multivariate logistic regression analysis, increasing hospital volume was associated with lower odds of in-hospital mortality (odds ratio [OR] = 0.31, 95% confidence interval [CI] = 0.02-0.95) and lower odds of discharge to a long-term care facility (OR = 0.00, 95% CI = 0.00-0.66). Increasing hospital volume was also associated with lower odds of blood transfusion (OR = 0.84, 95% CI = 0.72-0.94). Length of stay decreased with increasing hospital volume (P = .03). CONCLUSIONS: Patient safety may be maximized when renal ablation is performed at high-volume centers as a result of both greater procedural experience and potentially multidisciplinary triage and periprocedural management.

Socioeconomic position, health behaviors, and racial disparities in cause-specific infant mortality in Michigan, USA.

OBJECTIVES: Studies about racial disparities in infant mortality suggest that racial differences in socioeconomic position (SEP) and maternal risk behaviors explain some, but not all, excess infant mortality among Blacks relative to non-Hispanic Whites. We examined the contribution of these to disparities in specific causes of infant mortality. METHODS: We analyzed data about 2,087,191 mother-child dyads in Michigan between 1989 and 2005. First, we calculated crude Black-White infant mortality ratios independently and by specific cause of death. Second, we fit multivariable Poisson regression models of infant mortality, overall and by cause, adjusting for SEP and maternal risk behaviors. Third, Crude Black-White mortality ratios were compared to adjusted predicted probability ratios, overall and by specific cause. RESULTS: SEP and maternal risk behaviors explained nearly a third of the disparity in infant mortality overall, and over 25% of disparities in several specific causes including homicide, accident, sudden infant death syndrome, and respiratory distress syndrome. However, SEP and maternal risk behaviors had little influence on disparities in other specific causes, such as septicemia and congenital anomalies. CONCLUSIONS: These findings help focus policy attention toward disparities in those specific causes of infant mortality most amenable to social and behavioral intervention, as well as research attention to disparities in specific causes unexplained by SEP and behavioral differences.

Social Environments, Genetics, and Black-White Disparities in Infant Mortality.

BACKGROUND: Genes and environments often interplay to produce population health. However, in some instances, the scientific literature has favoured one explanation, underplaying the other, even in the absence of rigorous support. We examine parental race disparity on the risk of infant mortality to see if such an analysis might provide clues to understanding the extent to which genes and environment may shape perinatal risks. METHODS: We assessed parental racial disparities in infant mortality among singletons by analysing the risk of infant mortality among racially consonant vs. dissonant couples over time between 1989-1997 and 1998-2006 in the state of Michigan (n = 1 428 199). We calculated the degree of modification of the relation between maternal race and infant mortality by paternal race dynamically across the two time periods. RESULTS: Infant mortality among interracial couples decreased with time relative to white-white couples, while infant mortality among black-black couples increased with time after adjusting for socio-economic, demographic, and prenatal care differences. The degree to which paternal black race strengthened the relation between maternal black race and higher infant mortality risk relative to white mothers increased with time throughout our study. CONCLUSIONS: Evidence from these data suggests that environmental factors likely play the greater role in explaining the parental race disparity and risk of infant mortality.

Disparities in imaging utilization for acute ischemic stroke based on patient insurance status.

OBJECTIVE: Previous studies have shown socioeconomic disparities in imaging utilization for both acute and chronic diseases. We studied a nationwide database to determine whether insurance-based disparities exist in the utilization of imaging for acute ischemic stroke. MATERIALS AND METHODS: Inpatients with a primary diagnosis of acute ischemic stroke from November 2005 through December 2011 were identified from the Perspective database. Patients were stratified into four groups according to insurance status as follows: uninsured, Medicaid, Medicare, and private insurance. Utilization rates of head CT, perfusion CT, head MRI, noninvasive head angiography (including head CT angiography [CTA] and head MR angiography [MRA]), noninvasive neck angiography (including neck CTA and neck MRA), carotid ultrasound, and echocardiography were compared using a chi-square test. A multivariable logistic regression model adjusting for potential confounding variables was fit to determine the association between insurance status and imaging utilization. RESULTS: A total of 210,212 patients were included in this study: 10,396 patients (5.0%) were uninsured, 14,243 patients (6.8%) had Medicaid, 153,209 patients (72.9%) had Medicare, and 32,364 patients (15.4%) had private insurance. Even after we had controlled for confounding variables, significant disparities existed in imaging utilization. Compared with patients with private insurance, uninsured patients had significantly lower odds of noninvasive head angiography (odds ratio [OR] = 0.78, 95% CI = 0.74-0.81, p < 0.0001), neck angiography (OR = 0.79, 95% CI = 0.76-0.83, p < 0.0001), and head MRI (OR = 0.77, 95% CI = 0.74-0.81, p < 0.0001). The same was true for Medicaid and Medicare patients. CONCLUSION: Disparities exist in the utilization of noninvasive head and neck imaging, MRI, and echocardiography for patients with acute ischemic stroke based on patient insurance status. More research is needed to understand these disparities.

Are network-based interventions a useful antiobesity strategy? An application of simulation models for causal inference in epidemiology.

Recent research suggests that social networks may present an avenue for intervention against obesity. By using a simulation model in which artificial individuals were nested in a social network, we assessed whether interventions targeting highly networked individuals could help reduce population obesity. We compared the effects of targeting antiobesity interventions at the most connected individuals in a network with those targeting individuals at random. We tested 2 interventions, the first "preventing" obesity among 10% of the population at simulation outset and the second "treating" obesity among 10% of the obese population yearly, each in 2 separate simulations. One simulation featured a literature-based parameter for the network spread of obesity, and the other featured an artificially high parameter. Interventions that targeted highly networked individuals did not outperform at-random interventions in simulations featuring the literature-based parameter. However, in simulations featuring the artificially high parameter, the targeted prevention intervention outperformed the at-random intervention, whereas the treatment intervention implemented at random outperformed the targeted treatment intervention. Results were qualitatively similar across network topologies and intervention scales. Although descriptive studies suggest that social networks influence the spread of obesity, policies targeting well-connected individuals in social networks may not improve obesity reduction. We highlight and discuss the potential applications of counterfactual simulations in epidemiology.

Rethinking our public health genetics research paradigm.

Since the sequencing of the human genome, tremendous resources have been dedicated to understanding how genetic determinants may drive the production of disease. Despite some successes, the promise of genetics research in these areas remains largely unrealized. The focus on isolating individual (or clusters of) genes that may be associated with narrowly defined phenotypes in large part explains this discrepancy. In particular, efforts to identify genotypes associated with narrow phenotypes force the field to use study designs that capitalize on homogeneous samples to minimize the potential for competing influences or confounders, which imposes important limitations on understanding the role of genes in human health. We argue that a population health genetics that incorporates genetics into large, multiwave, multilevel cohorts has the best potential to clarify how genes, in combination and with the environment, jointly influence population health.

Infant mortality among Arab-Americans: findings from the Arab-American birth outcomes study.

Arab-Americans (AAs) have lower risk of preterm birth relative to Non-Arab Whites. This has been attributed to lower likelihood of birth out of wedlock, maternal tobacco use during pregnancy, and foreign maternal birthplace among AAs. We were interested in understanding the roles of these and other demographic factors in the etiology of infant mortality among this group. Using data about all live, singleton births between 1989 and 2005 in the state with the highest proportion of AAs in the US, we calculated infant mortality (death prior to 1 year of life) for AAs and Non-Arab Whites. To clarify the etiology of potential differences in infant mortality, we also assessed infant mortality sub-categories, including neonatal mortality (death prior to 28 days of life) and post-neonatal mortality (death between 28 and 365 days of life). We fit trivariable and multivariable logistic regression models adjusted for explanatory covariates to assess each covariate's contributions to the relation between ethnicity and infant mortality. AAs had a lower infant mortality rate (4.7 per 1,000 live births) than non-Arab Whites (5.6 per 1,000 live births), overall (odds ratio = 0.84, 95% confidence interval: 0.74-0.96). In trivariable models, adjusting for marital status, maternal tobacco consumption during pregnancy, and maternal birthplace each separately attenuated the bivariate ethnicity-mortality relation to non-significance. Our findings suggest that lower risk of infant mortality among AAs relative to non-Arab Whites may be explained by differences in demographic characteristics and parental behavioral practices between them.

In-hospital mortality among patients with takotsubo cardiomyopathy: a study of the National Inpatient Sample 2008 to 2009.

BACKGROUND: Takotsubo cardiomyopathy is characterized by acute, reversible left ventricular apical ballooning. Little is known about the characteristics of patients with takotsubo cardiomyopathy who have in-hospital mortality. We sought to determine in-hospital mortality rate, complication rate, and characteristics of patients with in-hospital mortality related to takotsubo cardiomyopathy. METHODS: Patients diagnosed with takotsubo cardiomyopathy in the National Inpatient Database Samples 2008 to 2009 using International Classification of Diseases, Ninth Revision, code 42983 were included in this study. Our primary outcome was in-hospital mortality. In patients with takotsubo cardiomyopathy, we assessed demographic factors, the prevalence and associated mortality of underlying critical illnesses (acute ischemic stroke, sepsis, acute renal failure, respiratory insufficiency, and noncardiac surgery), and acute complications (acute congestive heart failure, respiratory insufficiency with congestive heart failure, cardiogenic shock, ventricular fibrillation/cardiac arrest, and intraaortic balloon pump placement). RESULTS: A total of 24,701 patients with takotsubo cardiomyopathy were identified. In-hospital mortality rate was 4.2%. A total of 21,994 patients (89.0%) were female. Male patients had a higher mortality rate than females (8.4% vs 3.6%, P < .0001). Age and race were not associated with mortality. Of patients with in-hospital mortality, 81.4% had underlying critical illnesses. Male patients with takotsubo had higher incidence of underlying critical illnesses than their female counterparts (36.6% vs 26.8%, P < .0001). CONCLUSIONS: The presence of underlying critical illness was the main driver of mortality, as these patients comprised >80% of patients with in-hospital mortality. Male patients, who were significantly more likely to have underlying critical illness, had significantly higher mortality rates than female patients. The presence of underlying critical illness likely explains the higher mortality rate among male patients.

Temporal changes in socioeconomic influences on health: maternal education and preterm birth.

OBJECTIVES: To consider how the relationships between social determinants and health indicators change over time, we assessed the time-varying influence of maternal education on risk of preterm birth (PTB) between 1989 and 2006. METHODS: We used bivariate and multivariable Poisson regression models with robust variation estimates to examine (1) the association between maternal education and PTB risk by year; (2) the relationship between low maternal education and PTB, late PTB, and very PTB risk by year relative to 1989; and (3) the relationship between high maternal education and PTB, late PTB, and very PTB risk by year relative to 1989. RESULTS: After adjustment, PTB risk increased among the most educated and did not change among the least educated women over time. Risk of PTB among the least educated relative to the most educated women decreased with time. Late PTB risk increased among both the most and the least educated groups but more among the most educated. CONCLUSIONS: Maternal education may be becoming less protective against PTB. The influence of the social determinants of health is dynamic, warranting revisions of our understanding of their roles over time.

Social network analysis and agent-based modeling in social epidemiology.

The past five years have seen a growth in the interest in systems approaches in epidemiologic research. These approaches may be particularly appropriate for social epidemiology. Social network analysis and agent-based models (ABMs) are two approaches that have been used in the epidemiologic literature. Social network analysis involves the characterization of social networks to yield inference about how network structures may influence risk exposures among those in the network. ABMs can promote population-level inference from explicitly programmed, micro-level rules in simulated populations over time and space. In this paper, we discuss the implementation of these models in social epidemiologic research, highlighting the strengths and weaknesses of each approach. Network analysis may be ideal for understanding social contagion, as well as the influences of social interaction on population health. However, network analysis requires network data, which may sacrifice generalizability, and causal inference from current network analytic methods is limited. ABMs are uniquely suited for the assessment of health determinants at multiple levels of influence that may couple with social interaction to produce population health. ABMs allow for the exploration of feedback and reciprocity between exposures and outcomes in the etiology of complex diseases. They may also provide the opportunity for counterfactual simulation. However, appropriate implementation of ABMs requires a balance between mechanistic rigor and model parsimony, and the precision of output from complex models is limited. Social network and agent-based approaches are promising in social epidemiology, but continued development of each approach is needed.

Unevenly distributed: a systematic review of the health literature about socioeconomic inequalities in adult obesity in the United Kingdom.

BACKGROUND: There is a growing literature documenting socioeconomic inequalities in obesity risk among adults in the UK, with poorer groups suffering higher risk. METHODS: In this systematic review, we summarize and appraise the extant peer-reviewed literature about socioeconomic inequalities in adult obesity risk in the UK published between 1980 and 2010. Only studies featuring empirical assessments of relations between socioeconomic indicators and measures of obesity among adults in the UK were included. RESULTS: A total of 35 articles met inclusion criteria, and were reviewed here. CONCLUSION: Socioeconomic indicators of low socioeconomic position (SEP), including occupational social class of the head-of-household at birth and during childhood, earlier adulthood occupational social class, contemporaneous occupational social class, educational attainment, and area-level deprivation were generally inversely associated with adult obesity risk in the UK. Measures of SEP were more predictive of obesity among women than among men. We outline important methodological limitations to the literature and recommend avenues for future research.

Differences in Health Characteristics of Geographic Subgroups of Arab Americans in a Northern California Health Plan.

INTRODUCTION: Arab Americans are a diverse ethnic group originating from a large geographic area in the Middle East and North Africa (MENA). We aim to characterize differences in health between Arab Americans from different geographic subgroups within MENA. METHODS: We used cross-sectional electronic health record (EHR) data for a subset of 4913 Arab Americans aged 20-84 in a 2016 Northern California health plan study cohort who could be assigned to one of 4 geographic subgroups (Gulf, African, Levant, and Other) based on EHR ethnicity data. We calculated age-adjusted prevalence estimates for men and women and used generalized linear models to compare Gulf, African, and Other subgroups to Levant Arabs on risk factors (obesity and smoking), chronic conditions (diabetes, hypertension, hyperlipidemia, and asthma), and mental health (depression and anxiety). RESULTS: Among women, prevalence of smoking was lower among Gulf, African, and Other Arabs than Levant Arabs. Among men, prevalence of obesity, diabetes, and hyperlipidemia was lower among Gulf, African, and Other Arabs than Levant Arabs, while prevalence of depression was higher for these subgroups than Levant Arabs. DISCUSSION: We found substantial differences in health characteristics across Arab Americans from different geographic subgroups. Our results suggest that more detailed race and ethnicity information should be collected on Arab Americans to better understand their diverse health risks.