Health status, neighborhood socioeconomic context, and premature mortality in the United States: The National Institutes of Health-AARP Diet and Health Study

Objectives. We examined whether the risk of premature mortality associated with living in socioeconomically deprived neighborhoods varies according to the health status of individuals.Methods. Community-dwelling adults (n = 566 402; age = 50–71 years) in 6 US states and 2 metropolitan areas participated in the ongoing prospective National Institutes of Health–AARP Diet and Health Study, which began in 1995. We used baseline data for 565 679 participants on health behaviors, self-rated health status, and medical history, collected by mailed questionnaires. Participants were linked to 2000 census data for an index of census tract socioeconomic deprivation. The main outcome was all-cause mortality ascertained through 2006.Results. In adjusted survival analyses of persons in good-to-excellent health at baseline, risk of mortality increased with increasing levels of census tract socioeconomic deprivation. Neighborhood socioeconomic mortality disparities among persons in fair-to-poor health were not statistically significant after adjustment for demographic characteristics, educational achievement, lifestyle, and medical conditions.Conclusions. Neighborhood socioeconomic inequalities lead to large disparities in risk of premature mortality among healthy US adults but not among those in poor health.Research dating back to at least the 1920s has shown that the United States has experienced persistent and widening socioeconomic disparities in premature mortality over time.^1–5 However, it has been unclear whether socioeconomic inequalities affect the longevity of persons in good and poor health equally. Socioeconomic status (SES) and health status are interrelated,^6–8 and both are strong independent predictors of mortality.⁹ Low SES is associated with greater risk of ill health and premature death,^{1–5,8,10–13} partly attributable to disproportionately high prevalence of unhealthful lifestyle practices^10,14,15 and physical and mental health conditions.^13,16 Correspondingly, risk of premature mortality is higher in poor than in more affluent areas.^16,17 Although the association between neighborhood poverty and mortality is independent of individual-level SES,^17,18 aggregation of low-SES populations in poor areas may contribute to variations in health outcomes across neighborhoods. Conversely, economic hardships resulting from ill health may lead persons in poor physical or mental health to move to poor neighborhoods.¹⁹ This interrelatedness may create spurious associations between neighborhood poverty and mortality.Although previous studies have found that the risk of premature death associated with poor health status varies according to individuals'' SES,^20,21 no published studies have examined whether the relative risks for premature mortality associated with living in neighborhoods with higher levels of socioeconomic deprivation vary by health status of individuals. Clarifying these relationships will inform social and public health policies and programs that aim to mitigate the health consequences of neighborhood poverty.^22,23We used data from a large prospective study to examine whether the risk of premature mortality associated with neighborhood socioeconomic context differs according to health status at baseline and remains after adjustment for person-level risk factors for mortality, such as SES, lifestyle practices, and chronic medical illnesses.     

Racial/Ethnic and Socioeconomic Differences in Short-Term Breast Cancer Survival Among Women in an Integrated Health System

Objectives. We examined the combined influence of race/ethnicity and neighborhood socioeconomic status (SES) on short-term survival among women with uniform access to health care and treatment.Methods. Using electronic medical records data from Kaiser Permanente Northern California linked to data from the California Cancer Registry, we included 6262 women newly diagnosed with invasive breast cancer. We analyzed survival using multivariable Cox proportional hazards regression with follow-up through 2010.Results. After consideration of tumor stage, subtype, comorbidity, and type of treatment received, non-Hispanic White women living in low-SES neighborhoods (hazard ratio [HR] = 1.28; 95% confidence interval [CI] = 1.07, 1.52) and African Americans regardless of neighborhood SES (high SES: HR = 1.44; 95% CI = 1.01, 2.07; low SES: HR = 1.88; 95% CI = 1.42, 2.50) had worse overall survival than did non-Hispanic White women living in high-SES neighborhoods. Results were similar for breast cancer–specific survival, except that African Americans and non-Hispanic Whites living in high-SES neighborhoods had similar survival.Conclusions. Strategies to address the underlying factors that may influence treatment intensity and adherence, such as comorbidities and logistical barriers, should be targeted at low-SES non-Hispanic White and all African American patients.Breast cancer is the most common cancer among women in the United States, and it is the second leading cause of cancer death.1 Despite significant improvements in breast cancer survival from 1992 to 2009,1,2 racial/ethnic and socioeconomic survival disparities have persisted.3,4 African American women have consistently been found to have worse survival after breast cancer,3,5–11 Hispanic women have worse or similar survival,3,9,11,12 and Asian women as an aggregated group have better or similar survival3,9,11,12 than do non-Hispanic White women. Underlying factors thought to contribute to these racial/ethnic disparities include differences in stage at diagnosis,8,12,13 distributions of breast cancer subtypes,14–16 comorbidities,12,13,17 access to and utilization of quality care,13,18 and treatment.12,13Numerous studies also have found poorer survival after breast cancer diagnosis among women residing in neighborhoods of lower socioeconomic status (SES).6,9,19,20 Research has shown that inadequate use of cancer screening services, and consequent late stage diagnosis and decreased survival, contribute to the SES disparities.21,22 Similar to racial/ethnic disparities, SES disparities have been attributed to inadequate treatment and follow-up care and comorbidities.18 Previous population-based studies have continued to observe racial/ethnic survival disparities after adjusting for neighborhood SES, but these studies have not considered the combined influence of neighborhood SES and race/ethnicity.3,9,11,12,23 These disparities may remain because information on individual-level SES, health insurance coverage, comorbidities, quality of care, and detailed treatment regimens have typically not been available.3,8,9,11,13 Even among studies using national Surveillance Epidemiology and End Results–Medicare linked data, in which more detailed information on treatment and comorbidities are available among some patients aged 65 years and older, survival disparities have remained.12,23,24 However, not all data on medical conditions and health care services are captured in Medicare claims, including data on Medicare beneficiaries enrolled in HMOs (health maintenance organizations).25,26Using electronic medical records data from Kaiser Permanente Northern California (KPNC) linked to data from the population-based California Cancer Registry (CCR), we recently reported that chemotherapy use followed practice guidelines but varied by race/ethnicity and neighborhood SES in this integrated health system.27 Therefore, to overcome the limitations of previous studies and address simultaneously the multiple social28 and clinical factors affecting survival after breast cancer diagnosis, we used the linked KPNC–CCR database to determine whether racial/ethnic and socioeconomic differences in short-term overall and breast cancer–specific survival persist in women in a membership-based health system. Our study is the first, to our knowledge, to consider the combined influence of neighborhood SES and race/ethnicity and numerous prognostic factors, including breast cancer subtypes and comorbidities, thought to underlie these long-standing survival disparities among women with uniform access to health care and treatment.     

Posttraumatic Stress Disorder and Incident Heart Failure Among a Community-Based Sample of US Veterans

Objectives. We investigated the association between posttraumatic stress disorder (PTSD) and incident heart failure in a community-based sample of veterans.Methods. We examined Veterans Affairs Pacific Islands Health Care System outpatient medical records for 8248 veterans between 2005 and 2012. We used multivariable Cox regression to estimate hazard ratios and 95% confidence intervals for the development of heart failure by PTSD status.Results. Over a mean follow-up of 7.2 years, veterans with PTSD were at increased risk for developing heart failure (hazard ratio [HR] = 1.47; 95% confidence interval [CI] = 1.13, 1.92) compared with veterans without PTSD after adjustment for age, gender, diabetes, hyperlipidemia, hypertension, body mass index, combat service, and military service period. Additional predictors for heart failure included age (HR = 1.05; 95% CI = 1.03, 1.07), diabetes (HR = 2.54; 95% CI = 2.02, 3.20), hypertension (HR = 1.87; 95% CI = 1.42, 2.46), overweight (HR = 1.72; 95% CI = 1.25, 2.36), obesity (HR = 3.43; 95% CI = 2.50, 4.70), and combat service (HR = 4.99; 95% CI = 1.29, 19.38).Conclusions. Ours is the first large-scale longitudinal study to report an association between PTSD and incident heart failure in an outpatient sample of US veterans. Prevention and treatment efforts for heart failure and its associated risk factors should be expanded among US veterans with PTSD.Posttraumatic stress disorder (PTSD) is a psychiatric illness that affects approximately 7.7 million Americans aged older than 18 years.1 PTSD typically results after the experience of severe trauma, and veterans are at elevated risk for the disorder. The National Vietnam Veterans Readjustment Study reported the prevalence of PTSD among veterans who served in Vietnam as 15.2% among men and 8.1% among women.2 In fiscal year 2009, nearly 446 045 Veterans Administration (VA) patients had a primary diagnosis of PTSD, a threefold increase since 1999.3 PTSD is of growing clinical concern as evidence continues to link psychiatric illnesses to conditions such as arthritis,4 liver disease,5 digestive disease,6 and cancer.6 When the postwar health status of Vietnam veterans was examined, those with PTSD had higher rates of diseases of the circulatory, nervous, digestive, musculoskeletal, and respiratory systems.7The evidence linking PTSD to coronary heart disease (CHD) is substantial.8–10 Veterans with PTSD are significantly more likely to have abnormal electrocardiograph results, myocardial infarctions, and atrioventricular conduction deficits than are veterans without PTSD.11 In a study of 605 male veterans of World War II and the Korean War, CHD was more common among veterans with PTSD than among those without PTSD.12 Worldwide, adults exposed to the disaster at Chernobyl experienced increased rates of CHD up to 10 years after the event,13 and studies of stressors resulting from the civil war in Lebanon found elevated CHD mortality.14,15Although the exact biological mechanism by which PTSD contributes to CHD remains unclear, several hypotheses have been suggested, including autonomic nervous system dysfunction,16 inflammation,17 hypercoagulability,18 cardiac hyperreactivity,19 altered neurochemistry,20 and co-occurring metabolic syndrome.16 One of the hallmark symptoms of PTSD is hyperarousal,21 and the neurobiological changes brought on from sustained sympathetic nervous system activation affect the release of neurotransmitters and endocrine function.22 These changes have negative effects on the cardiovascular system, including increased blood pressure, heart rate, and cardiac output.22,23Most extant literature to date examining cardiovascular sequelae has shown a positive association between PTSD and coronary artery disease.8–10 Coronary artery disease is well documented as one of the most significant risk factors for future development of heart failure.24 Despite burgeoning evidence for the role of PTSD in the development of coronary artery disease, there are few studies specifically exploring the relationship between PTSD and heart failure. Limited data suggest that PTSD imparts roughly a threefold increase in the odds of developing heart failure in both the general population5 and in a sample of the elderly.25 These investigations, however, have been limited by cross-sectional study design, a small proportion of participants with PTSD, and reliance on self-reported measures for both PTSD and heart failure.5,25 Heart failure is a uniquely large public health issue, as nearly 5 million patients in the United States are affected and there are approximately 500 000 new cases each year.26 Identifying predictors of heart failure can aid in early detection efforts while simultaneously increasing understanding of the mechanism behind development of heart failure.To mitigate the limitations of previous investigations, we undertook a large-scale prospective study to further elucidate the role of prevalent PTSD and development of incident heart failure among veterans, while controlling for service-related and clinical covariates. Many studies investigating heart failure have relied on inpatient records; we leveraged outpatient records to more accurately reflect the community burden of disease.     

Life-Course Accumulation of Neighborhood Disadvantage and Allostatic Load: Empirical Integration of Three Social Determinants of Health Frameworks

Objectives. We examined if the accumulation of neighborhood disadvantages from adolescence to mid-adulthood were related to allostatic load, a measure of cumulative biological risk, in mid-adulthood, and explored whether this association was similar in women and men.Methods. Data were from the participants in the Northern Swedish Cohort (analytical n = 818) at ages 16, 21, 30, and 43 years in 1981, 1986, 1995, and 2008. Personal living conditions were self-reported at each wave. At age 43 years, 12 biological markers were measured to operationalize allostatic load. Registered data for all residents in the cohort participants’ neighborhoods at each wave were used to construct a cumulative measure of neighborhood disadvantage. Associations were examined in ordinary least-squares regression models.Results. We found that cumulative neighborhood disadvantage between ages 16 and 43 years was related to higher allostatic load at age 43 years after adjusting for personal living conditions in the total sample (B = 0.11; P = .004) and in men (B = 0.16; P = .004), but not in women (B = 0.07; P = .248).Conclusions. Our findings suggested that neighborhood disadvantage acted cumulatively over the life course on biological wear and tear, and exemplified the gains of integrating social determinants of health frameworks.Different frameworks relevant to social determinants of health have been introduced, developed, and applied to research during the last 2 decades. We specifically aimed to empirically integrate the allostatic load,1 neighborhoods and health,2 and life-course epidemiology3 frameworks by examining whether the life-course accumulation of neighborhood disadvantage was related to allostatic load in mid-adulthood.The allostatic load model4,5 was developed within the stress physiology field and was introduced as a general framework for the cumulative “wear and tear” the body eventually experiences across multiple interrelated physiological systems because of repeated stressor exposures during the life course. Allostatic load (or cumulative biological risk) has been proposed as a biological link that explains socioeconomic disparities in morbidity and mortality6,7; empirical studies have demonstrated that allostatic load is patterned by social determinants (e.g., ethnicity, education, and income)8–11 and prospectively predicts mortality as well as cognitive and physical decline.12–14Studying the importance of the area of residence—defined, for example, by parishes, wards, or neighborhoods—for health represents a more contextual perspective on social determinants of health. For example, socioeconomic status aggregated at the neighborhood level is related to cardiovascular health beyond individual-level socioeconomic conditions.2,15 Such effects have been attributed to several possible pathways, including (1) indirect-cognitive paths, where the effects are mediated by conscious responses such as health-damaging behaviors, and (2) direct-contextual paths, which include differential chronic stressor exposure and the potential development of allostatic load.16 Cross-sectional studies in recent years have demonstrated that various neighborhood characteristics, such as socioeconomic disadvantages,17 poverty,11 lack of affluence,18 and perceived neighborhood conditions,19 are related to allostatic load. However, most studies within the field use cross-sectional or short-term prospective designs20,21; conceptual and empirical elaborations of how social context affects health in the long term are lacking.21However, such a long-term temporal perspective emphasizes life-course epidemiology, which focuses on how and when exposures over the life course affect adult health outcomes, a question that is guided by conceptual life-course models.3 The cumulative risk model, which posits that the most important aspect for health effects is the accumulation of exposures across the life course, is the model with the most consistent empirical support (e.g., socioeconomic disadvantages and cardiovascular outcomes).22Although the few recent register-based studies on area effects on health over the life course found only a small proportion of variance in adult morbidity and mortality to be attributable to the area of residence at specific life-course periods,23 mortality risk clustered at the area of residence seemed to accumulate over the life course, corresponding to a cumulative risk life-course model.24 The cumulative risk model is also the model that most closely corresponds to the allostatic load framework, which emphasizes the gradual accumulation of physiological dysregulation over the life course.6 Empirical studies demonstrated that the life-course accumulation of individual socioeconomic disadvantages and of adversity from childhood or adolescence to mid-adulthood were related to allostatic load.25–27In summary, despite the unique contributions of research on the social determinants of health offered by allostatic load, neighborhoods and health, and the life-course epidemiology frameworks, empirical efforts to integrate them are at an early stage. To advance this task, the cumulative risk life-course model appears to be a promising focal point.The present 27-year prospective cohort study specifically aimed to examine whether socioeconomic disadvantages of the residence neighborhood at 4 time points during the life course were cumulatively related to allostatic load in mid-adulthood, when taking the life-course accumulation of disadvantageous personal living conditions into account. Previous research hypothesized that women were more embedded in their communities, and because of this, could be more exposed to neighborhoods stressors and health effects.28 Therefore, our secondary aim explored this cumulative effect on allostatic load separately in women and men.     

A Systematic Review of Neighborhood Disparities in Point-of-Sale Tobacco Marketing

We systematically reviewed evidence of disparities in tobacco marketing at tobacco retailers by sociodemographic neighborhood characteristics. We identified 43 relevant articles from 893 results of a systematic search in 10 databases updated May 28, 2014. We found 148 associations of marketing (price, placement, promotion, or product availability) with a neighborhood demographic of interest (socioeconomic disadvantage, race, ethnicity, and urbanicity).Neighborhoods with lower income have more tobacco marketing. There is more menthol marketing targeting urban neighborhoods and neighborhoods with more Black residents. Smokeless tobacco products are targeted more toward rural neighborhoods and neighborhoods with more White residents. Differences in store type partially explain these disparities.There are more inducements to start and continue smoking in lower-income neighborhoods and in neighborhoods with more Black residents. Retailer marketing may contribute to disparities in tobacco use. Clinicians should be aware of the pervasiveness of these environmental cues.Tobacco products and their marketing materials are ubiquitous in US retailers from pharmacies to corner stores.1 A similar presence is found across the globe, except in countries that ban point-of-sale (POS) tobacco marketing (e.g., Australia, Canada, Thailand2). In the United States, the POS has become the main communications channel for tobacco marketing3,4 and is reported as a source of exposure to tobacco marketing by more than 75% of US youths.5 Burgeoning evidence6,7 suggests that marketing at the POS is associated with youths’ brand preference,8 smoking initiation,9 impulse purchases,10,11 and compromised quit attempts.12,13The marketing of tobacco products is not uniform; it is clear from industry documents that the tobacco industry has calibrated its marketing to target specific demographic groups defined by race,14 ethnicity,15 income,16 mental health status,17 gender,18,19 and sexual orientation.20 Framed as an issue of social and environmental justice,14 research has documented historical racial, ethnic, and socioeconomic disparities in the presence of tobacco billboards,21–25 racial disparities in total tobacco marketing volume,24 and targeting of menthol cigarettes to communities with more Black residents.25,26 Targeted marketing of a consumer product that kills up to half27 of its users when used as directed exacerbates inequities in morbidity and mortality. Smoking is estimated to be responsible for close to half of the difference in mortality between men in the lowest and highest socioeconomic groups.28 However, evidence of marketing disparities is scattered across multiple disciplines and marketing outcomes, such as product availability, advertising quantity, presence of promotional discounts, and price. A synthesis of this literature would provide valuable information for intervention on tobacco marketing in the retail environment and inform etiological research on health disparities.To address this gap in the literature, we systematically reviewed observational studies that examined the presence and quantity of POS tobacco marketing to determine the extent to which marketing disparities exist by neighborhood demographic characteristic (i.e., socioeconomic disadvantage, race, ethnicity, and urbanicity).     

Clustering of Midlife Lifestyle Behaviors and Subsequent Cognitive Function: A Longitudinal Study

Objectives. We examined the association between individual and clustered lifestyle behaviors in middle age and later in cognitive functioning.Methods. Middle-aged participants (n = 2430) in the Supplémentation en Vitamines et Minéraux Antioxydant study self-reported their low physical activity, sedentary behavior, alcohol use, smoking, low fruit and vegetable consumption, and low fish consumption. We assessed cognition 13 years later via 6 neuropsychological tests. After standardization, we summed the scores for a composite cognitive measure. We estimated executive functioning and verbal memory scores using principal component analysis. We estimated the mean differences (95% confidence intervals [CIs]) in cognitive performance by the number of unhealthy behaviors using analysis of covariance. We identified latent unhealthy behavior factor via structural equation modeling.Results. Global cognitive function and verbal memory were linearly, negatively associated with the number of unhealthy behaviors: adjusted mean differences = −0.36 (95% CI = −0.69, −0.03) and −0.46 (95% CI = −0.80, −0.11), respectively, per unit increase in the number of unhealthy behaviors. The latent unhealthy behavior factor with low fruit and vegetable consumption and low physical activity as main contributors was associated with reduced verbal memory (RMSEA = 0.02; CFI = 0.96; P = .004). No association was found with executive functioning.Conclusions. Comprehensive public health strategies promoting healthy lifestyles might help deter cognitive aging.Noncommunicable diseases with notable lifestyle components are the leading causes of death worldwide.1,2 There is also growing evidence of the critical role of different midlife health and risk behaviors in cognitive aging.3–7 Because lifestyles are inherently modifiable and no treatment of cognitive decline is available, such findings argue for the paramount importance of prevention.8,9Current data support a deleterious effect of alcohol abstinence or abuse (compared with moderate alcohol consumption),10 smoking,7 low fruit and vegetable intake,11 low fish intake,12 and low physical activity (PA) levels13 on cognitive aging. However, it has been widely documented that lifestyle factors are strongly correlated with each other, forming a cluster of healthy or unhealthy behaviors.14 Traditionally, such interrelations have been accounted for by statistical adjustment; however, it is of major public health interest to consider the cumulative and combined effect of the various lifestyle behaviors on health by using multidimensional strategies.14Research that examines the combined effect of lifestyle factors on mortality is plentiful, and data have been colligated in a recent meta-analysis.15 These authors reported a 66% reduction in mortality risk by comparing adherence to 4 or more healthy lifestyle behaviors versus engagement in any number of unhealthy behaviors.The combined effect of lifestyle factors has also been explored in relation to cardiovascular diseases,16–18 cancer,18–22 diabetes,18,23 memory complaints,24 and dementia25–27; however, very few studies have reported findings regarding cognition.28,29 Despite heterogeneity in the definition of a healthy lifestyle, study design, and residual confounding, available, but scarce, data support a critical, protective role of healthy lifestyles in cognitive health through their beneficial properties via oxidative, inflammatory, vascular, and other neuroprotective pathways.30–33Our objectives in this study were to examine the association between individual and clustered lifestyle behaviors and later cognitive functioning. We employed traditional and innovative techniques (structural equation modeling) in our epidemiological pursuit.     

Impact of Rurality,Broiler Operations,and Community Socioeconomic Factors on the Risk of Campylobacteriosis in Maryland

Objectives. We evaluated the combined impact of community-level environmental and socioeconomic factors on the risk of campylobacteriosis.Methods. We obtained Campylobacter case data (2002–2010; n = 3694) from the Maryland Foodborne Diseases Active Surveillance Network. We obtained community-level socioeconomic and environmental data from the 2000 US Census and the 2007 US Census of Agriculture. We linked data by zip code. We derived incidence rate ratios by Poisson regressions. We mapped a subset of zip code–level characteristics.Results. In zip codes that were 100% rural, incidence rate ratios (IRRs) of campylobacteriosis were 6 times (IRR = 6.18; 95% confidence interval [CI] = 3.19, 11.97) greater than those in urban zip codes. In zip codes with broiler chicken operations, incidence rates were 1.45 times greater than those in zip codes without broilers (IRR = 1.45; 95% CI = 1.34, 1.58). We also observed higher rates in zip codes whose populations were predominantly White and had high median incomes.Conclusions. The community and environment in which one lives may significantly influence the risk of campylobacteriosis.Campylobacter is a leading cause of bacterial gastroenteritis in much of the developed and developing world.1,2 In addition to the diarrhea and vomiting associated with gastroenteritis, infection with Campylobacter can lead to more serious sequelae, such as Guillain-Barré syndrome, a demyelinating autoimmune disorder that can sometimes lead to death.3 Scallan et al.4 estimated that Campylobacter causes approximately 845 000 domestically acquired illnesses in the United States each year, along with 8463 hospitalizations and 76 deaths. Although the majority of these illnesses are estimated to be foodborne,4 attributing specific infections to specific sources has been challenging.Commonly reported risk factors for Campylobacter outbreaks include exposure to undercooked poultry,5 unpasteurized milk,6,7 and contaminated water.8 Eating in restaurants,9 not observing proper food preparation practices,10 and traveling abroad9,11 have also been associated with both outbreaks and sporadic (nonoutbreak) cases of campylobacteriosis. Additional risk factors for sporadic infections include contact with pets,5,12 contact with farm animals and livestock,13,14 and contact with animal feces.15 Significant associations of living in rural areas with risk of campylobacteriosis also have been identified in Europe and Canada.16–18 Moreover, a specific feature of rural environments—animal density—has been identified as a significant predictor of Campylobacter incidence in Canada and New Zealand.16,17Several sociodemographic risk factors for campylobacteriosis have also been identified, the 2 most consistent being gender (males) and age (< 5 years).8,16–19 Previous studies have also evaluated socioeconomic factors associated with the incidence of Campylobacter infection, and the findings suggest that these infections may occur more frequently among individuals characterized by higher socioeconomic status.16,20 Moreover, Samuel et al.21 reported that the incidence of campylobacteriosis among African Americans was lower than that among other ethnic groups across multiple sites in the United States, although hospitalization rates for this group were higher. These findings, however, may be influenced by differentials in illness reporting among varying races and ethnic groups.Nonetheless, these previous reports have largely resulted from population-based case–control studies focused on individual-level data. To our knowledge, no US study has examined the combined effect of community-level environmental and socioeconomic risk factors on the risk of campylobacteriosis. Such an analysis can be useful in (1) identifying (and possibly predicting) “hot spot” communities that bear high burdens of this illness, and (2) addressing significant research gaps concerning potential health disparities in the risk of infectious diseases.22 We linked Maryland Foodborne Diseases Active Surveillance (FoodNet) data to US Census data and US Department of Agriculture Census of Agriculture data at the zip code level to evaluate associations between community-level environmental and socioeconomic risk factors and the incidence of Campylobacter infections in Maryland.     

Lesbian,Gay, Bisexual,and Transgender Hate Crimes and Suicidality Among a Population-Based Sample of Sexual-Minority Adolescents in Boston

Objectives. We examined whether past-year suicidality among sexual-minority adolescents was more common in neighborhoods with a higher prevalence of hate crimes targeting lesbian, gay, bisexual, and transgender (LGBT) individuals.Methods. Participants’ data came from a racially/ethnically diverse population-based sample of 9th- through 12th-grade public school students in Boston, Massachusetts (n = 1292). Of these, 108 (8.36%) reported a minority sexual orientation. We obtained data on LGBT hate crimes involving assaults or assaults with battery between 2005 and 2008 from the Boston Police Department and linked the data to the adolescent’s residential address.Results. Sexual-minority youths residing in neighborhoods with higher rates of LGBT assault hate crimes were significantly more likely to report suicidal ideation (P = .013) and suicide attempts (P = .006), than were those residing in neighborhoods with lower LGBT assault hate crime rates. We observed no relationships between overall neighborhood-level violent and property crimes and suicidality among sexual-minority adolescents (P > .05), providing evidence for specificity of the results to LGBT assault hate crimes.Conclusions. Neighborhood context (i.e., LGBT hate crimes) may contribute to sexual-orientation disparities in adolescent suicidality, highlighting potential targets for community-level suicide-prevention programs.Suicide is the second-leading cause of death among all youths worldwide and is the third-leading cause of death among all youths in the United States,1 making the topic of adolescent suicidality a global public health and medical priority.2 One of the most consistent findings in psychiatric epidemiology is the existence of marked sexual orientation disparities in adolescent suicidality (e.g., suicidal ideation and suicide attempts).3 Lesbian, gay, bisexual, and transgender (LGBT, or sexual minority) adolescents are more likely to contemplate,4–6 plan,7 and attempt4,5,8 suicide than their heterosexual peers, and these disparities have been documented across multiple countries.4,5,8Despite the increased attention devoted to eliminating sexual orientation disparities in adolescent suicide, a 2011 report from the Institute of Medicine on LGBT health disparities noted the dearth of research into determinants of adverse health outcomes, including suicidality, within this population.9 To date, research has focused predominantly on individual (e.g., hopelessness, depressed mood),5,8,10–13 peer (e.g., recent suicide attempts by a peer, peer victimization),5,8,14,15 family (e.g., family rejection, family abuse),5,8,13,16–18 and school (e.g., presence of gay–straight alliances in schools, school safety)14,18,19 factors that are associated with suicidality among sexual-minority adolescents, which mirrors research on adolescent suicidality more broadly.20 This research has offered key insights into determinants of suicide risk, but sexual orientation–related disparities in suicidality remain after control for these established risk factors.4,5,8 The persistence of these disparities indicates the importance of considering additional risk factors, including at the social-ecological level, which we define as influences that occur above individuals, peers, families, and schools, including neighborhoods as well as institutional practices and policies (e.g., state policies that ban same-sex marriage).21,22Decades of research in medical sociology and social epidemiology have provided substantial evidence for the role that broad social-ecological factors play in shaping population health,23,24 and Healthy People 2020 recognizes that such factors may be implicated in LGBT health.25 Yet there is a paucity of research into the social-ecological risk factors for suicide among sexual-minority adolescents. In one of the few studies to address this topic, Hatzenbuehler26 created an ecological measure of the social environment surrounding lesbian, gay, and bisexual youths living in counties across the state of Oregon. Compared with lesbian, gay, and bisexual youths living in counties with supportive environments, the risk of attempting suicide was 20% higher among sexual-minority youths in less-supportive environments,26 suggesting that ecological measures can reveal previously unrecognized social determinants of suicide risk among sexual-minority adolescents. However, additional research on other social-ecological factors that may influence suicide risk within this population is warranted.Therefore, in the current study, we used a novel measure of the social environment: neighborhood-level hate crimes targeting LGBT persons. Hate crimes refer to “unlawful, violent, destructive or threatening conduct in which the perpetrator is motivated by prejudice toward the victim’s putative social group.”27^(p480) Evidence demonstrates that many sexual minorities experience hate crimes28; data from the Federal Bureau of Investigation demonstrated that 17.4% of the 88 463 hate crimes between the years of 1995 and 2008 targeted sexual minorities,29 a rate that was more than 8 times what would be expected when one considers the relatively low percentage of sexual minorities in the general population.30The objective of the present study was to examine whether suicidal ideation and suicide attempts among sexual-minority adolescents are more common in neighborhoods with a higher prevalence of hate crimes targeting LGBT individuals. Although there is limited research on the relationship between neighborhood-level LGBT hate crimes and suicidality among sexual-minority populations, existing research suggests strong associations between neighborhood-level exposure to violence and suicide in general (i.e., non-LGBT) populations.31,32 On the basis of this literature, we hypothesized higher rates of suicidal ideation and attempts among sexual minority adolescents residing in neighborhoods with more LGBT hate crimes. To test this hypothesis, we obtained LGBT hate crimes data from the Boston Police Department Community Disorders Unit and linked this information to individual-level data on suicidality (i.e., ideation and attempts) and sexual orientation from a population-based sample of Boston, Massachusetts, adolescents. This study therefore capitalizes on a rare opportunity to examine a potentially salient social-ecological risk factor for suicidality among sexual-minority adolescents.     

Social Branding to Decrease Smoking Among Young Adults in Bars

Objectives. We evaluated a Social Branding antitobacco intervention for “hipster” young adults that was implemented between 2008 and 2011 in San Diego, California.Methods. We conducted repeated cross-sectional surveys of random samples of young adults going to bars at baseline and over a 3-year follow-up. We used multinomial logistic regression to evaluate changes in daily smoking, nondaily smoking, and binge drinking, controlling for demographic characteristics, alcohol use, advertising receptivity, trend sensitivity, and tobacco-related attitudes.Results. During the intervention, current (past 30 day) smoking decreased from 57% (baseline) to 48% (at follow-up 3; P = .002), and daily smoking decreased from 22% to 15% (P < .001). There were significant interactions between hipster affiliation and alcohol use on smoking. Among hipster binge drinkers, the odds of daily smoking (odds ratio [OR] = 0.44; 95% confidence interval [CI] = 0.30, 0.63) and nondaily smoking (OR = 0.57; 95% CI = 0.42, 0.77) decreased significantly at follow-up 3. Binge drinking also decreased significantly at follow-up 3 (OR = 0.64; 95% CI = 0.53, 0.78).Conclusions. Social Branding campaigns are a promising strategy to decrease smoking in young adult bar patrons.Tobacco companies1 and public health authorities2–5 recognize young adulthood as a critical time when experimenters either quit or transition to regular tobacco use. Young adults are also aspirational role models for youths.1,6,7 Tobacco companies devote considerable resources to reaching young adults to encourage tobacco use,1,8–11 and young adults have a high prevalence of smoking.12 In California in 2011, young adults had the highest smoking prevalence of any age group, and the Department of Health estimated that 32% of California smokers started smoking between the ages of 18 and 26 years.13 Although they are more likely to intend to quit and successfully quit than older adults,14–17 young adults are less likely to receive assistance with smoking cessation.18,19 Although there are few proven interventions to discourage young adult smoking,20 cessation before age 30 years avoids virtually all of the long-term adverse health effects of smoking.21Tobacco companies have a long history of using bars and nightclubs to reach young adults and to encourage smoking.1,6,9–11,22–24 Bar attendance and exposure to tobacco bar marketing is strongly associated with smoking.25 The 1998 Master Settlement Agreement and Food and Drug Administration regulations that limit tobacco advertising to youths, explicitly permit tobacco marketing in “adult only” venues, including bars and nightclubs.26,27Aggressive tobacco marketing may actually be more intensive in smoke-free bars: a 2010 study of college students attending bars found that students in the community with a smoke-free bar law were more likely to be approached by tobacco marketers, offered free gifts, and to take free gifts for themselves than in communities without a smoke-free bar law.28 Bars and nightclubs also attract young adults who are more likely to exhibit personality traits such as sensation seeking,29 increasing their risk30 independently of receptivity to tobacco advertising; tobacco promotional messages resonate with these personality traits.8,31 Tobacco marketing campaigns are tailored to specific segments of the population defined by psychographics (e.g., values, attitudes, shared interests, such as tastes in music and fashion, and friend groups) and demographic criteria, and they aim to create positive smoker images, identities, and social norms for smoking.1,8 Tobacco marketing campaigns also focus on young adult trendsetters to leverage peer influence to promote smoking.6,10In contrast to the tobacco companies’ efforts, most young adult health interventions take place in colleges or health centers rather than social environments.32–39 Bars and nightclub venues represent an opportunity to reach those at highest risk for long-term smoking morbidity and mortality.40 We evaluated the effectiveness of an intervention to decrease cigarette smoking by countering tobacco industry marketing strategies targeting young adults attending bars and nightclubs in the San Diego, California, “hipster” scene. Because tobacco and alcohol use are strongly linked,41,42 we also examined the effects of the intervention on alcohol use and among binge drinkers. We found a significant decrease in smoking in the community where the intervention took place, including significant decreases among nondaily smokers and binge drinkers, as well as a significant decrease in binge drinking.     

Longitudinal Predictors of Human Papillomavirus Vaccination Among a National Sample of Adolescent Males

Objectives. We conducted a longitudinal study to examine human papillomavirus (HPV) vaccine uptake among male adolescents and to identify vaccination predictors.Methods. In fall 2010 and 2011, a national sample of parents with sons aged 11 to 17 years (n = 327) and their sons (n = 228) completed online surveys. We used logistic regression to identify predictors of HPV vaccination that occurred between baseline and follow-up.Results. Only 2% of sons had received any doses of HPV vaccine at baseline, with an increase to 8% by follow-up. About 55% of parents who had ever received a doctor’s recommendation to get their sons HPV vaccine did vaccinate between baseline and follow-up, compared with only 1% of parents without a recommendation. Fathers (odds ratio = 0.29; 95% confidence interval = 0.09, 0.80) and non-Hispanic White parents (odds ratio = 0.29; 95% confidence interval = 0.11, 0.76) were less likely to have vaccinated sons. Willingness to get sons HPV vaccine decreased from baseline to follow-up among parents (P < .001) and sons (P = .003).Conclusions. Vaccination against HPV remained low in our study and willingness to vaccinate may be decreasing. Physician recommendation and education about HPV vaccine for males may be key strategies for improving vaccination.Quadrivalent human papillomavirus (HPV) vaccine against types 6, 11, 16, and 18 is approved to protect against genital warts (caused mostly by HPV types 6 and 111) and anal cancer (caused mostly by HPV types 16 and 182) in males.3 About 4% of men in the United States report a previous diagnosis of genital warts,4 and about 2250 new cases of anal cancer occur annually among males in the United States.5 Given the high levels of HPV concordance among sexual partners,6 vaccinating males may also have indirect health benefits for their partners.7 United States guidelines began including HPV vaccine for males in October 2009.8 The Advisory Committee on Immunization Practices first provided a permissive recommendation, recommending the 3-dose quadrivalent vaccine series for males aged 9 to 26 years but not making it part of their routine vaccination schedule.8 In October 2011, the Advisory Committee on Immunization Practices updated its stance on HPV vaccine for males and recommended routine vaccination of boys aged 11 to 12 years with catch-up vaccination for males aged 13 to 21 years.9 The updated recommendation continues to allow HPV vaccine to be given to males aged as young as 9 years and up to 26 years.9Although numerous studies have examined HPV vaccine uptake among females,10 data on HPV vaccine uptake among males are sparse. Despite mostly encouraging early levels of parental acceptability of the vaccine for males,11–13 initial estimates found that only about 2% of male adolescents in the United States had received any doses of HPV vaccine by the end of 2010.14,15 Recent data suggest that this increased to about 8% by the end of 2011.16 We are not aware of any studies that have examined predictors of vaccine uptake among males.Our study addresses several important gaps in the existing literature. We provide the first longitudinal examination of HPV vaccination among males and identify predictors of vaccine uptake. In doing so, we used data from both parents and their adolescent sons because many adolescents are involved in vaccination decisions.17 We also examined longitudinal changes in vaccine acceptability among parents and sons and parents’ reasons for not getting their sons HPV vaccine, because these data may provide valuable insight about future HPV vaccine uptake among males.     

Intergenerational relationships between the smoking patterns of a population-representative sample of US mothers and the smoking trajectories of their children

Objectives. We assessed intergenerational transmission of smoking in mother-child dyads.Methods. We identified classes of youth smoking trajectories using mixture latent trajectory analyses with data from the Children and Young Adults of the National Longitudinal Survey of Youth (n = 6349). We regressed class membership on prenatal and postnatal exposure to maternal smoking, including social and behavioral variables, to control for selection.Results. Youth smoking trajectories entailed early-onset persistent smoking, early-onset experimental discontinued smoking, late-onset persistent smoking, and nonsmoking. The likelihood of early onset versus late onset and early onset versus nonsmoking were significantly higher among youths exposed prenatally and postnatally versus either postnatally alone or unexposed. Controlling for selection, the increased likelihood of early onset versus nonsmoking remained significant for each exposure group versus unexposed, as did early onset versus late onset and late onset versus nonsmoking for youths exposed prenatally and postnatally versus unexposed. Experimental smoking was notable among youths whose mothers smoked but quit before the child''s birth.Conclusions. Both physiological and social role-modeling mechanisms of intergenerational transmission are evident. Prioritization of tobacco control for pregnant women, mothers, and youths remains a critical, interrelated objective.Women who smoke during pregnancy are more likely to have offspring who become adolescent smokers.^1–7 Studies link mother''s smoking during pregnancy with youths'' earlier smoking initiation,^3,7–9 greater persistence in regular smoking,^3,7 and stronger nicotine dependency.^6,8,10,11Hypothesized physiological pathways for mother-to-child transmission of smoking are reviewed elsewhere^12–14 and may include inherited susceptibility to addiction alone or in combination with in utero neurodevelopmental exposure and scarring that activates nicotine susceptibility. Furthermore, because few women who smoke during pregnancy quit after delivery^15,16 higher rates of smoking among offspring may reflect role modeling of maternal smoking behavior. Notably, parental smoking is hypothesized to demonstrate pro-smoking norms and solidify pro-smoking attitudes.^17,18Studies considering both smoking during pregnancy and subsequent maternal smoking outcomes have sought to distinguish between these proposed social and physiological transmission pathways.^{1–4,6,7,9,19} Similarly, studies controlling for family sociodemographic factors^{1,2,4,5,7,8,10,11,19,20} or maternal propensity for health or risk taking^1,2,9,10 have sought to further distinguish direct physiological or social transmission from selection. Studies considering children''s cognitive and behavioral outcomes have shown that selection by maternal social and behavioral precursors to smoking during pregnancy strongly biases findings on smoking during pregnancy^21,22; however, it remains unclear whether this is also the case for youth smoking. Some studies^2,3,5,6,19 have observed that smoking during pregnancy operates independently of subsequent maternal smoking. A few have found that smoking during pregnancy is only independently associated in select analyses (e.g., for initiation but not frequency or number of cigarettes^6,9 or only among females^7,20). Several have found that smoking during pregnancy does not operate independently of subsequent maternal smoking behavior,^1,4 and the remaining studies do not address postnatal maternal smoking.^8,9,11We explored whether these inconsistencies in findings supporting social or physiological mechanisms for intergenerational transmission can be accounted for by more comprehensively examining maternal and child smoking behavior. Previous work has established the advantages of statistical models for youth smoking trajectories that capture initiation, experimentation, cessation, or continued use.^23–28 Studies focusing on parental smoking concurrent with youth smoking suggest that postnatal exposures may differentially predispose youths for specific smoking trajectories.^24,26–28 Only 3 known studies have considered whether smoking during pregnancy influences youth smoking progression, and these have shown greater likelihood of early regular use^3,11 and telescoping to dependence.⁸ However, limitations of sample selectivity and measurement and modeling of maternal and youth smoking outcomes restrict the generalizability and scope of these findings.²⁹ To specifically address these limitations and more comprehensively assess hypothesized intergenerational transmission pathways, we used US population–representative data, latent variable techniques, and a rich set of data on maternal and youth smoking and social and behavioral selection factors. We characterized trajectories of youth smoking from adolescence through young adulthood and considered exposure to various maternal smoking patterns from prebirth to the child''s early adolescence.     

Let’s Get Physical: Sexual Orientation Disparities in Physical Activity,Sports Involvement,and Obesity Among a Population-Based Sample of Adolescents

Objectives. We examined sexual orientation disparities in physical activity, sports involvement, and obesity among a population-based adolescent sample.Methods. We analyzed data from the 2012 Dane County Youth Assessment for 13 933 students in grades 9 through 12 in 22 Wisconsin high schools. We conducted logistic regressions to examine sexual orientation disparities in physical activity, sports involvement, and body mass index among male and female adolescents.Results. When we accounted for several covariates, compared with heterosexual females, sexual minority females were less likely to participate in team sports (adjusted odds ratio [AOR] = 0.44; 95% confidence interval [CI] = 0.37, 0.53) and more likely to be overweight (AOR = 1.28; 95% CI = 1.02, 1.62) or obese (AOR = 1.88; 95% CI = 1.43, 2.48). Sexual minority males were less likely than heterosexual males to be physically active (AOR = 0.62; 95% CI = 0.46, 0.83) or to participate in team sports (AOR = 0.26; 95% CI = 0.20, 0.32), but the 2 groups did not differ in their risk of obesity.Conclusions. Sexual orientation health disparities in physical activity and obesity are evident during adolescence. Culturally affirming research, interventions, and policies are needed for sexual minority youths.Obesity is an increasing and serious health problem among adolescents.1,2 This is of major concern because obesity has many health and social consequences and it affects adolescents’ overall well-being.3,4 Obesity among adolescents also has a high likelihood of continuing into adulthood.5 Recent population-based and longitudinal research has demonstrated that there are disparities in obesity between sexual minority and heterosexual adolescents.6–8 Research has also documented sexual orientation disparities in physical activity and sports involvement in adolescence.9,10 Despite this increased attention, the overall empirical base remains limited, and findings also suggest some gender nuances that need further exploration. More population-based research is needed to investigate these disparities, consistent with federal health priorities.7,11There are sexual orientation–based disparities in physical activity and sports involvement among adolescents; however, there are mixed findings for females. One study reported that sexual minority females are less likely than heterosexual females to participate in moderate to vigorous physical activity and team sports,9 whereas another study found no such differences in physical activity.10 Findings are more consistent for sexual minority male adolescents, who are less likely than heterosexual males to engage in moderate to vigorous physical activity, to engage in recommended levels of physical activity, and to participate in team sports.9,10 More research is needed because of the paucity of studies and mixed results. This is especially important given that adolescents’ physical activity has been shown to relieve stress and protect against many mental and physical health conditions, including obesity,12,13 for which sexual minority adolescents are at greater risk.Research on sexual orientation disparities in obesity suggests that there are some gender nuances. Many studies have found that sexual minority female adolescents have higher risk of obesity than heterosexual females (e.g., higher body mass index [BMI], defined as weight in kilograms divided by the square of height in meters).6,8,10,14 These sexual orientation disparities in obesity among adolescent females parallel those among sexual minority adult women.15,16Findings of elevated obesity risk among sexual minority male adolescents are mixed. Some studies show that sexual minority males, specifically bisexual males, have higher odds of obesity than heterosexuals,14 whereas other studies have documented no differences.10 By contrast, some studies have found that heterosexual males have increases in BMI during adolescence compared with sexual minority males.6,8 These mixed findings for sexual minority males might be attributed to physical maturation and developmental changes in adolescence that some of the cross-sectional studies could not examine.10,14 Specifically, one study found that sexual minority males had higher obesity risk than heterosexual males in early adolescence, but their risk of obesity became lower than for heterosexual males later in adolescence.6 The authors postulated that, compared with heterosexual males, sexual minority males reach puberty maturation earlier in adolescence but make less substantial weight gains later in adolescence.6Sexual orientation health disparities have been explained through the minority stress model: sexual minority youths experience unique stressors and stigma related to their sexual identity (e.g., homophobic bullying), which lead to poorer health.17 Sexual minority adolescents might therefore be less likely to be physically active or involved in team sports because of potential minority stressors that they often experience at school, especially bias and heightened discrimination experienced in the context of sports or in their communities.18–20 More recently, the negative effects of minority stress and stigma on physical health disparities have been documented,21,22 including their effects on obesity for sexual minority women.23 However, the minority stress model is not sufficient in explaining how sexual minority adolescent females, but not males, are at greater risk for obesity compared with their heterosexual peers.Another potential explanation of these obesity disparities is related to cultural norms and sexual minority females’ experiences of internalizing ideals for femininity and appearance8 and sexual minority males’ ideals for muscularity and body image.24 For instance, compared with heterosexual women, sexual minority women are more likely to be satisfied with their bodies and attracted to women with greater body mass,25,26 whereas sexual minority men are less likely to be satisfied with their bodies compared with heterosexual men and are more likely to be attracted to muscular men.25,27 Therefore, these 2 groups might engage (or not engage) in differing body weight management and dieting behaviors compared with their heterosexual peers; concomitantly, these behaviors might render differing risks for obesity.Sexual minority adolescents’ lack of physical activity and sports involvement might be influenced by traditional gender norms associated with athleticism and sports, which has implications for their athletic self-esteem and involvement. For adolescent males, team sports are a means to define masculinity28; however, adolescent males often engage in homophobic banter to prove their masculinity and heterosexuality and to enforce traditional gender norms.29,30 Sexual prejudice is pervasive in athletic settings,19,20 making sports contexts unwelcoming and unsafe for many sexual minority males. Traditional feminine gender norms and homophobia also affect sexual minority females’ involvement in sports.31 However, sexual minority adolescent females have unique gendered experiences in relation to sports. Because women’s athleticism can be a stereotype for being a lesbian,32 sexual minority females might avoid sports involvement. Expecting or experiencing exclusion in sports settings might also affect sexual minority adolescents’ athletic self-esteem, consequently preventing them from engaging in future sports or physical activity.9 In fact, athletic self-esteem has been found to contribute to sexual orientation disparities in sports involvement and physical activity.9Emerging evidence of sexual orientation disparities in physical activity, sports involvement, and obesity among adolescents, in addition to potential gender nuances in these disparities, points to the need for more population-based research in this area. We therefore examined sexual orientation disparities among a large adolescent population-based sample and tested for gender differences. While accounting for variables commonly associated with physical activity and obesity among adolescents,4,33 we hypothesized that sexual minority adolescents would be less likely to report physical activity and sports involvement than would their heterosexual peers. We also hypothesized that sexual minority females would be at higher risk for being overweight and obese than their heterosexual peers. Because of mixed findings in existing sexual orientation disparities research among adolescent males, we hypothesized that sexual minority males would be at equal risk for being overweight and obese than their heterosexual male peers.     

Latent Tuberculosis Infection Screening in Foreign-Born Populations: A Successful Mobile Clinic Outreach Model

Objectives. We evaluated the efficacy of a mobile medical clinic (MMC) screening program for detecting latent tuberculosis infection (LTBI) and active tuberculosis.Methods. A LTBI screening program in a MMC in New Haven, Connecticut, used medical surveys to examine risk factors and tuberculin skin test (TST) screening eligibility. We assessed clinically relevant correlates of total (prevalent; n = 4650) and newly diagnosed (incident; n = 4159) LTBI from 2003 to 2011.Results. Among 8322 individuals, 4159 (55.6%) met TST screening eligibility criteria, of which 1325 (31.9%) had TST assessed. Similar to LTBI prevalence (16.8%; 779 of 4650), newly diagnosed LTBI (25.6%; 339 of 1325) was independently correlated with being foreign-born (adjusted odds ratio [AOR] = 8.49; 95% confidence interval [CI] = 5.54, 13.02), Hispanic (AOR = 3.12; 95% CI = 1.88, 5.20), Black (AOR = 2.16; 95% CI = 1.31, 3.55), employed (AOR = 1.61; 95% CI = 1.14, 2.28), and of increased age (AOR = 1.04; 95% CI = 1.02, 1.05). Unstable housing (AOR = 4.95; 95% CI = 3.43, 7.14) and marijuana use (AOR = 1.57; 95% CI = 1.05, 2.37) were significantly correlated with incident LTBI, and being male, heroin use, interpersonal violence, employment, not having health insurance, and not completing high school were significantly correlated with prevalent LTBI.Conclusions. Screening for TST in MMCs successfully identifies high-risk foreign-born, Hispanic, working, and uninsured populations and innovatively identifies LTBI in urban settings.Foreign-born populations are at greatest risk for having both latent tuberculosis infection (LTBI) and developing tuberculosis (TB) disease within high-income countries and, in 2012, accounted for 63.0% of the 9951 TB cases in the United States.1 Newly diagnosed and reactivated TB infection among foreign-born individuals in the United States is currently 12 times greater (15.8 vs 1.4 cases per 100 000 population) than among US-born persons.1 Among foreign-born individuals, LTBI often reactivates within 5 to 10 years after arrival to the United States.2,3 Undocumented migrants and visitors from high-TB-prevalence countries, however, do not undergo routine LTBI screening and thus remain outside traditional health care screening and treatment programs in primary or specialty care settings except when they are acutely ill.3,4 Thus, identifying and treating LTBI cases among these high-risk populations before transforming to TB disease and resultant transmission to others is crucial to ending the cycle of ongoing TB infection within the United States.Workplace screening,4,5 mandatory criminal justice system screening,6–8 screening for entry into medication-assisted therapy and drug treatment programs,9 and refugee and naturalization programs10,11 have been successful for reaching legal and domestic populations, but innovative options are needed to target foreign-born populations that are not yet integrated into mainstream care.Culturally and geographically isolated foreign-born groups may be overlooked especially if there is low self-perception of tuberculosis risk.12 Tuberculin skin testing (TST), though imperfect, is internationally recognized and has been shown to be a reasonably accurate assessment of LTBI status in immunocompetent adults, despite receiving previous Bacillus Calmette-Guérin vaccine.13 Whereas other studies have focused on traditional clinics or statewide programs,14 we present an innovative mobile medical clinic (MMC) as a model to target “hidden” foreign-born populations for LTBI screening.New Haven, Connecticut, the country’s fourth poorest city for its size, with a census of 130 000, is a medium-sized urban setting in New England that has experienced extraordinary social and medical disparities including a high prevalence of poverty, drug addiction, HIV/AIDS, and unemployment and is disproportionately comprised of people of color, including 35.4% and 27.4% being Black or Hispanic, respectively.15 As New Haven is an industrial city with low-paying jobs, there has been an influx of foreign-born people, now officially comprising 11.6% of the population, with many having an undocumented residency status. Health care access for this group is absent unless individuals pay directly for fee-for-service, and concern for deportation and arrest further hinders willingness to seek care.16The Community Health Care Van (CHCV) is an MMC that provides free health care 5 days per week in 4 impoverished neighborhoods in New Haven. Though at inception the program was linked to the needle and syringe exchange program,17 it has since expanded over 20 years to become a vital bridge to a diverse array of health and addiction treatment services that includes services for medically underserved populations, including directly administered antiretroviral therapy to treat HIV,18–21 buprenorphine maintenance therapy,22–25 community transitional programs from the criminal justice system,26–33 hepatitis B vaccination,34 rapid hepatitis C screening,35 and other ongoing primary health care programs such as screening and monitoring of sexually transmitted infections,36 diabetes, and hypertension. In addition, the CHCV provides outreach and intensive case management services.37 Screening for LTBI and TB disease began in 2003 to target high-risk undocumented and foreign-born clients, as well as clients entering drug treatment programs or homeless shelters, who were concerned about TB infection yet were reluctant to seek care in traditional health care settings for fear of deportation, prohibitive cost, or language barriers. The LTBI screening program shortly thereafter became successfully incorporated into the country’s first mobile buprenorphine maintenance therapy program.9     

Prevalence of HCV Infection Among Clients in Community-Based Health Settings in Hawaii, 2002–2010: Assessing Risk Factors

Objectives. We sought to determine the prevalence of HCV infection and identify risk factors associated with HCV infection among at-risk clients presenting to community-based health settings in Hawaii.Methods. Clients from 23 community-based sites were administered risk factor questionnaires and screened for HCV antibodies from December 2002 through May 2010. We performed univariate and multivariate logistic regression analyses.Results. Of 3306 participants included in the analysis, 390 (11.8%) tested antibody positive for HCV. Highest HCV antibody prevalence (17.0%) was in persons 45 to 64 years old compared with all other age groups. Significant independent risk factors were current or prior injection drug use (P < .001), blood transfusion prior to July 1992 (P = .002), and having an HCV-infected sex partner (P = .03). Stratification by gender revealed sexual exposure to be significant for males (P = .001).Conclusions. Despite Hawaii’s ethnic diversity, high hepatocellular carcinoma incidence, and a statewide syringe exchange program in place since the early 1990s, our HCV prevalence and risk factor findings are remarkably consistent with those reported from the mainland United States. Hence, effective interventions identified from US mainland population studies should be generalizable to Hawaii.Hepatitis C is the most prevalent chronic blood-borne viral infection in the United States, with an estimated 1.3% of the population chronically infected.1 Chronic HCV infection is often asymptomatic; approximately 75% of infected persons may be unaware that they are infected.2 Transmission is mainly through direct blood-to-blood contact, and the most common risk factor in the United States is the sharing of injection drug use equipment.1,2 Complications from HCV infection include cirrhosis, hepatocellular carcinoma (HCC), and end-stage liver disease; more than one third of liver transplants in the United States can be attributed to HCV.3 There is currently no vaccine,4 and until recently, standard therapy with pegylated interferon and ribavirin achieved a sustained virologic response in only 40% to 50% of patients.5,6In May 2011, the US Food and Drug Administration approved 2 new HCV-specific protease inhibitors for the treatment of chronic genotype 1 HCV infections: boceprevir7,8 and telaprevir.9,10 In combination with standard therapy, these drugs have achieved significantly higher rates of sustained virologic response: up to 67% to 75%.7,10 Achieving sustained virologic response is key to reducing mortality, HCC, and other comorbidities.11,12 With such a large percentage of HCV-infected individuals unaware of their status and new successful treatments available, there is now increased rationale for health providers to screen their clients for chronic HCV infection.The population of Hawaii differs from that of the mainland United States on a number of key factors related to HCV and HCC. Hawaii has the highest incidence of HCC nationally.13 Asian/Pacific Islanders have the highest incidence of HCC in the United States,13 and 57% of the Hawaii’s population is Asian, either alone or in combination with other ethnic groups.14 The high HCC incidence among Asian/Pacific Islanders is attributed in large part to chronic hepatitis B virus (HBV) infection,13,15 and the identification and treatment of persons with chronic HBV or HCV infection is an important public health priority in Hawaii. In addition, Hawaii implemented a statewide syringe exchange program in the early 1990s, the first state to do so.16 The risk factor demonstrating the strongest association with HCV infection in the United States is injection drug use,1,17 and syringe exchange programs have demonstrated efficacy in reducing HCV infection among injection drug users.18,19To our knowledge, only 3 HCV prevalence studies have been conducted in Hawaii; however, each focused on a specific well-defined subgroup population: patients with HCC,20 HIV-infected persons enrolled in a state drug assistance plan,21 and adults from a homeless shelter.22The Adult Viral Hepatitis Prevention Program of the Hawaii State Department of Health, which offers risk-based HCV antibody testing based on reported national risk factors,1,23 has been collecting data on persons undergoing screening since 2002. We investigated the prevalence of HCV antibody positivity among at-risk clients of community-based health programs in Hawaii and identified demographic characteristics and independent risk factors associated with HCV infection.     

Neighborhoods and obesity in later life

Objectives. We examined the influence of neighborhood environment on the weight status of adults 55 years and older.Methods. We conducted a 2-level logistic regression analysis of data from the 2002 wave of the Health and Retirement Study. We included 8 neighborhood scales: economic advantage, economic disadvantage, air pollution, crime and segregation, street connectivity, density, immigrant concentration, and residential stability.Results. When we controlled for individual- and family-level confounders, living in a neighborhood with a high level of economic advantage was associated with a lower likelihood of being obese for both men (odds ratio [OR] = 0.86; 95% confidence interval [CI] = 0.80, 0.94) and women (OR = 0.83; 95% CI = 0.77, 0.89). Men living in areas with a high concentration of immigrants and women living in areas of high residential stability were more likely to be obese. Women living in areas of high street connectivity were less likely to be overweight or obese.Conclusions. The mechanisms by which neighborhood environment and weight status are linked in later life differ by gender, with economic and social environment aspects being important for men and built environment aspects being salient for women.Over the past few decades the prevalence of obesity has been rising for men and women across all age groups, including the elderly.¹ For example, in 2001 to 2002 in the United States, about 1 in 3 adults 60 years or older was obese.² This trend raises concerns because excess weight is associated with a number of chronic health conditions, including diabetes, high blood pressure, asthma, and arthritis.³ Moreover, obesity can have very important implications for publicly financed health care.⁴ Recent research suggests that a number of demographic, socioeconomic, and family factors⁵ influence obesity, but the role of the neighborhood context has not been fully explored.Excess weight results from an energy imbalance in which caloric intake exceeds energy expenditures, the latter closely related to physical activity. The neighborhood environment may influence energy intake (through its influence on food availability⁶) and energy expenditure (by facilitating or impeding physical activity). For example, the presence of supermarkets in the neighborhood is associated with higher fruit and vegetable intake,⁷ whereas eating at fast-food restaurants is associated with a high-fat diet and higher body mass index (BMI; weight in kilograms divided by height in meters squared).⁸ In terms of physical activity, individuals living in neighborhoods with less crime,^9–13 higher land-use mix,¹⁴ higher street connectivity,^11,14,15 higher residential density,^11,14 a greater number of destinations,^9,16 better aesthetics,^9,10,17 and sidewalks^10,12,17,18 tend to walk more often.^19,20Only a handful of studies linking neighborhood features to late-life obesity have focused on older adults.^{11,13,16,21–23} National studies are particularly lacking for the elderly. Yet evidence from national studies of adults of all ages suggests plausible connections between obesity and neighborhood factors. Using the 1990 to 1994 waves of the National Health Interview Survey, for example, Boardman et al.²⁴ found that adults residing in neighborhoods with a high concentration of poverty and in neighborhoods with a high percentage of Blacks were more likely to be obese. In another study, Robert and Reither²⁵ found that higher community socioeconomic disadvantage was related to higher BMI among women but not among men. Because these studies had very limited characterizations of the neighborhoods, the mechanism through which poor neighborhoods result in obesity remains unclear. It could be, for instance, that poor neighborhoods tend to have fewer supermarkets^26–28 and more-limited access to places for physical activity.^29,30Using a large, nationally representative survey, we examined the relationship between the economic, built, and social environments and weight status among men and women 55 years and older. We included 8 previously validated neighborhood scales reflecting neighborhood safety and segregation, concentration of immigrants, air pollution, residential stability, connectivity, density or access, and high and low neighborhood socioeconomic status.³¹ We modeled both obesity and overweight status by using multilevel modeling techniques in which we controlled for detailed individual- and family-level confounders.     

Meta-analysis of All-Cause Mortality According to Serum 25-Hydroxyvitamin D

We examined the relationship between serum 25-hydroxyvitamin D (25[OH]D) and all-cause mortality. We searched biomedical databases for articles that assessed 2 or more categories of 25(OH)D from January 1, 1966, to January 15, 2013. We identified 32 studies and pooled the data.The hazard ratio for all-cause mortality comparing the lowest (0–9 nanograms per milliliter [ng/mL]) to the highest (> 30 ng/mL) category of 25(OH)D was 1.9 (95% confidence interval = 1.6, 2.2; P < .001). Serum 25(OH)D concentrations less than or equal to 30 ng/mL were associated with higher all-cause mortality than concentrations greater than 30 ng/mL (P < .01).Our findings agree with a National Academy of Sciences report, except the cutoff point for all-cause mortality reduction in this analysis was greater than 30 ng/mL rather than greater than 20 ng/mL.An inverse association was proposed between solar irradiance and incidence of colon and breast cancer, based on a mechanism involving insufficient vitamin D. Individuals with lower serum 25-hydroxyvitamin D (25[OH]D) have higher risk of breast1–3 and colon cancer,4–6 other specific cancers,7 all invasive cancers combined,8 and coronary heart disease.9,10 Physiological mechanisms for the inverse association of 25(OH)D with cancer have been reported.11Despite research on the association between low vitamin D status and many diseases,12 no consensus has emerged on the optimal serum 25(OH)D concentration. The concern is whether it is safe to maintain serum 25(OH)D concentrations in the range high enough to prevent some types of cancers13–15 and coronary heart disease.9,10We decided to analyze the strength and consistency of the inverse association between levels of serum 25(OH)D and age-adjusted mortality hazard ratios in a rapidly expanding field of public health. A previous meta-analysis summarized 12 studies,16 another summarized 14,17 and another summarized a broader range.18We hypothesized that lower serum 25(OH)D was associated with higher all-cause mortality hazard ratios, and defined the age-adjusted hazard ratio for death from any cause as the outcome addressed by the meta-analysis. This analysis includes all studies of all-cause mortality hazard ratios by categories of serum 25(OH)D in healthy or general medical clinic cohorts that met the eligibility criteria. Twenty new studies of serum 25(OH)D and all-cause mortality entered the literature since the Zittermann et al. review,17 for a total of 32 in this review.19–50 Two studies in the review by Zittermann et al. did not meet the stringent inclusion criterion of the present study, and were not included.     

Loose Cigarette Purchasing and Nondaily Smoking Among Young Adult Bar Patrons in New York City

Objectives. We examined loose cigarette (loosie) purchasing behavior among young adult (aged 18–26 years) smokers at bars in New York City and factors associated with purchase and use.Methods. Between June and December 2013, we conducted cross-sectional surveys (n = 1916) in randomly selected bars and nightclubs. Using multivariable logistic regression models, we examined associations of loose cigarette purchasing and use with smoking frequency, price, social norms, cessation behaviors, and demographics.Results. Forty-five percent (n = 621) of nondaily smokers and 57% (n = 133) of daily smokers had ever purchased a loosie; 15% of nondaily smokers and 4% of daily smokers reported that their last cigarette was a loosie. Nondaily smokers who never smoked daily were more likely than were daily smokers to have last smoked a loosie (odds ratio = 7.27; 95% confidence interval = 2.35, 22.48). Quitting behaviors and perceived approval of smoking were associated with ever purchasing and recently smoking loosies.Conclusions. Loosie purchase and use is common among young adults, especially nondaily smokers. Smoking patterns and attitudes should be considered to reduce loose cigarette purchasing among young adults in New York City.Widespread adoption of clean indoor air laws and cigarette tax increases denormalize smoking behavior1 and decrease smoking rates.2,3 Although increasing taxes is one of the most effective means of smoking prevention and reduction,3 the increased price of cigarettes can also lead to tax-avoidant behaviors, such as buying untaxed packs smuggled from states with lower cigarette taxes and purchasing loose cigarettes, or “loosies.”4–6 In New York City (NYC), where a cigarette pack costs about $11.50, it has become common for smokers to purchase discounted packs and individual cigarettes from street peddlers and friends.7,8Much of the research exploring loosie purchasing in the United States has focused on underage or low-income minority populations, often in urban areas.7,9,10 One study found that in early 1993, 70% of stores in central Harlem sold loosies to minors.7 Another study conducted with a 2005–2006 convenience sample in inner-city Baltimore found that 77% of African American smokers aged 18 to 24 years had purchased loosies in the past month.11 Similarly, loosie purchasing in Mexico was more common among younger smokers with lower incomes.12Availability and visibility of loosies can promote smoking and encourage relapse.13 We defined nondaily smokers as those who smoked on 1 to 29 of the past 30 days.14,15 Shiffman et al. found that nondaily smokers were more likely than daily smokers to report that social and environmental stimuli motivated their smoking behavior.16 More specifically, cues such as taste, smell, social goading to smoke, and specific situations (e.g., smoking after meals) are more likely to be reported as motivators to smoke by nondaily smokers than by daily smokers.16 Because social–environmental cues have substantial impact on nondaily smokers’ motivation to smoke, it is likely that the cue of seeing loosies in one’s environment also motivates nondaily smokers to smoke.16Previous research substantiates this claim, with 1 study showing that people who regularly saw loosies available for purchase were more likely to be current smokers.17 Therefore, the widespread availability of loosies may have a greater impact on nondaily smokers. Nondaily smokers make up a third of US smokers,18,19 and nondaily smoking is increasingly common among young adults.20 Many young adults who smoke on only some days do not self-identify as smokers,21 and nondaily smoking is frequently paired with alcohol consumption.22–24 Nondaily and light smoking carry a lower, but substantial, risk for lung cancer and a similar risk as does daily smoking for cardiovascular disease.25–27 Occasional smokers also have higher smoking-related morbidity and mortality than do people who have never smoked.26,28–30Nondaily smoking can be a long-term behavior pattern31,32 or a transition to or from daily smoking.31 Nondaily smokers include different subgroups that may have very different smoking patterns or motivations to quit.33,34 Nondaily smokers who previously smoked daily have been defined in previous research as converted nondaily smokers. Nondaily smokers who have never smoked daily are defined as native nondaily smokers.18,19 Important differences exist between these subgroups of smokers: converted nondaily smokers are more likely to quit smoking than are native nondaily smokers and daily smokers,18,19 although most converted and native nondaily smokers were unable to remain abstinent for more than 90 days.19Loosie purchasing and use may play an important role in promoting continued tobacco use among nondaily smokers. The 2010 NYC Community Health Survey35 found that more than one third (34%) of young adult nondaily smokers (aged 18–26 years) reported that their last cigarette smoked was a loosie, compared with 14% of young adult daily smokers. Another study of NYC adults demonstrated that nondaily smokers were more likely to purchase loose cigarettes than were light and heavy smokers.36 To the best of our knowledge, little is known about the factors associated with loosie purchasing among nondaily smokers in the United States.We sought to better understand the factors associated with loosie purchasing among NYC young adults, specifically to determine (1) loosie purchase and use rates among converted nondaily, native nondaily, and daily smokers; (2) whether loosie purchase or use are associated with perceived social norms of smoking behavior; and (3) whether loosie purchasing is associated with smoking cessation intention or behavior.     

Socioeconomic Status and Bullying: A Meta-Analysis

We examined whether socioeconomic status (SES) could be used to identify which schools or children are at greatest risk of bullying, which can adversely affect children’s health and life.We conducted a review of published literature on school bullying and SES. We identified 28 studies that reported an association between roles in school bullying (victim, bully, and bully-victim) and measures of SES. Random effects models showed SES was weakly related to bullying roles. Adjusting for publication bias, victims (odds ratio [OR] = 1.40; 95% confidence interval [CI] = 1.24, 1.58) and bully-victims (OR = 1.54; 95% CI = 1.36, 1.74) were more likely to come from low socioeconomic households. Bullies (OR = 0.98; 95% CI = 0.97, 0.99) and victims (OR = 0.95; 95% CI = 0.94, 0.97) were slightly less likely to come from high socioeconomic backgrounds.SES provides little guidance for targeted intervention, and all schools and children, not just those with more socioeconomic deprivation, should be targeted to reduce the adverse effects of bullying.Bullying is defined as repeated, harmful behavior, characterized by an imbalance of power between the victim and perpetrator(s).1 There is compelling evidence that school bullying affects children’s health and well being, with the effects lasting long into adulthood.2,3 Victims of school bullying are at greater risk of physical and mental health problems,4,5 including depression,6,7 anxiety,8,9 psychotic or borderline personality symptoms,10,11 and are more likely to self-harm and attempt suicide.12,13 A small proportion of victims are classified as bully-victims, children who are victimized by their peers, but who also bully other children. Bully-victims are at even greater risk for maladjustment,5 exhibiting attention and behavioral difficulties,4,14 displaying poor social skills,15,16 and reporting increased levels of depression and anxiety through adolescence and into adulthood.2 By contrast, the negative outcomes of bullying perpetration are less clear. Bullies have been found more likely to engage in delinquent or antisocial behavior17,18; however, once other family and childhood risk factors are taken into account, they do not appear to be at any greater risk for poorer health, criminal, or social outcomes in adulthood.3Up to one third of children are involved in bullying, as bully, victim, or bully-victim,19,20 and when considered alongside the damaging effects on physical and mental health, bullying can be seen as a major public health concern.21 Identifying risk factors for bullying aids potential efforts in targeting resources, which can prevent youths from becoming involved in bullying, but also limits the impact it has on their health and well being. Traditional risk factors, such as age and gender, show a clear association22,23; however, there are a range of other potential determinants whose relationship to bullying remain unclear. One such determinant is socioeconomic status (SES), which shows some links to bullying, but at present, research findings are inconsistent regarding roles (i.e., bully, victim, or bully-victim).SES is an aggregate concept comprising resource-based (i.e., material and social resources) and prestige-based (individual’s rank or status) indicators of socioeconomic position, which can be measured across societal levels (individual, household, and neighborhood) and at different periods in time.24 It can be assessed through individual measures, such as education, income, or occupation,25,26 but also through composite measures that combine or assign weights to different socioeconomic aspects to provide an overall index of socioeconomic level. There is no standard measure of SES; indicators are used to measure specific aspects of socioeconomic stratification.26 Accordingly, different measures of SES may show varying effects, which can result from differing causal pathways, or through interactions with other social characteristics, such as gender or race.27 The multifaceted nature of SES has resulted in a lack of consistency in how researchers measure its relationship to bullying, and although several studies provide individual assessments of this relationship, as yet there is no clear consensus over whether roles in bullying are associated with individual socioeconomic measures, or in general, with SES.Currently, the literature suggests some link between low SES and victims or bully-victims at school.28,29 Specifically, being a victim has been reported to be associated with poor parental education,30,31 low parental occupation,32 economic disadvantage,33,34 and poverty.35 In addition, several studies found that bully-victims are also more likely to come from low socioeconomic backgrounds,29,30 including low maternal education28 and maternal unemployment.36 However, others found little or no association between SES and victims or bully-victims.37–39 The type of bullying may matter in relation to SES. Victims of physical and relational bullying have been found to more often come from low affluence families, whereas victims of cyber bullying have not.40Compared with victimization, few studies have explored the link between SES and bullying others. Some studies found bullying others to be associated with low SES, including economic disadvantage,34 poverty,35 and low parental education.30 Additionally, where composite measures have been used, children from low socioeconomic backgrounds have been found to bully others slightly more often.29,41 By contrast, others found no association between bullying perpetration and measures of SES.38,39,42There is a small but growing body of literature that examines the relationship between bullying and SES, and although findings tend to suggest that victims, bully-victims, and bullies are more likely to come from low socioeconomic backgrounds, the results are far from conclusive. First, studies differ in their approach to measuring SES; some use composite measures, combining multiple indicators such as parental education, wealth, and occupation, whereas others concentrate on a single socioeconomic indicator, most often parental education, affluence, or occupation. How bullying relates to SES may differ according to which socioeconomic indicator is used; therefore, in interpreting results, one must consider not only how bullying relates to SES in general, but also which socioeconomic indicator was used, and how this may have influenced the result. Furthermore, although several studies indicate an association between bullying and low SES, the reported effect sizes vary greatly across studies, with some reporting weak and others moderate to strong associations. So far, the associations between bullying and SES have not been quantified across a range of studies in a systematic way. To address this gap in the literature, we conducted a systematic review and meta-analysis that aimed to determine more precisely the exact nature and strength of the relationship between SES and bullying. We systematically investigated the association between the role taken in school bullying (victim, bully, or bully-victim) and measures of SES.