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.     

Socioeconomic Status and Lung Cancer: Unraveling the Contribution of Genetic Admixture

Objectives. We examined the relationship between genetic ancestry, socioeconomic status (SES), and lung cancer among African Americans and Latinos.Methods. We evaluated SES and genetic ancestry in a Northern California lung cancer case–control study (1998–2003) of African Americans and Latinos. Lung cancer case and control participants were frequency matched on age, gender, and race/ethnicity. We assessed case–control differences in individual admixture proportions using the 2-sample t test and analysis of covariance. Logistic regression models examined associations among genetic ancestry, socioeconomic characteristics, and lung cancer.Results. Decreased Amerindian ancestry was associated with higher education among Latino control participants and greater African ancestry was associated with decreased education among African lung cancer case participants. Education was associated with lung cancer among both Latinos and African Americans, independent of smoking, ancestry, age, and gender. Genetic ancestry was not associated with lung cancer among African Americans.Conclusions. Findings suggest that socioeconomic factors may have a greater impact than genetic ancestry on lung cancer among African Americans. The genetic heterogeneity and recent dynamic migration and acculturation of Latinos complicate recruitment; thus, epidemiological analyses and findings should be interpreted cautiously.Associations between socioeconomic status (SES) and cancer incidence or mortality and accompanying racial/ethnic differences are common findings across cancers and populations.1–9 An inverse association between socioeconomic measures and lung cancer incidence and mortality is a consistent observation among populations,7,10–18 especially among men, although for lung cancer mortality in the United States, this pattern is a reversal of that of earlier decades.19 Socioeconomic measurements are also known to vary across diverse populations.20 In the United States, African Americans and Latinos have, on average, lower education, larger household sizes, and lower income and are frequently unmarried compared with Whites.21–24 Smoking is more prevalent among people characterized by low socioeconomic factors such as low education, low income, and working-class occupations.20,25–27 Studies examining the relationship between SES and lung cancer, or cancer in general, have used surveys and registries with large sample sizes, thereby increasing the precision of effect estimates.7,11,12 However, these studies have been constrained by the lack of data on important risk factors for lung cancer11 or have linked aggregate socioeconomic exposure data to individual-level disease status.6,7,11 Ascribing attributes of a group to an individual may not be appropriate and can result in inaccurate inferences, especially if the exposure, SES, is misclassified.28,29Despite known disparities in lung cancer incidence30 and consistently observed associations between SES and both lung cancer and race/ethnicity, few studies have examined this interrelationship, which is thought to result from a complex interplay of environmental, social, economic, and genetic factors. Using incident cancer registry data, Krieger et al.31 observed an inverse relationship between lung cancer incidence and socioeconomic deprivation among African Americans but an increase in incidence with economic prosperity among Latinos. A study examining lung cancer among Latinos found that incidence increased as income increased and the percentage of Latinos residing in the census tract decreased.32 Many studies examining socioeconomic differences in lung cancer risk have suggested the increased risk cannot be fully explained by smoking, occupational, or dietary exposures,13,15,16,33,34 whereas others have found that controlling for several measures such as smoking,35 dietary fat, and perceived health removed associations with SES.17 Some studies examining racial/ethnic differences in lung cancer found ethnic differences disappeared after adjusting for SES.6,7,11 Together, these findings highlight the complexities of understanding the relationship among SES, lung cancer, and race/ethnicity.Self-reported race/ethnicity represents a combination of several factors—genetic, social, economic, and environmental.36 Moreover, because of the ancestral heterogeneity of Latinos and African Americans, self-reported race/ethnicity does not provide precise genetic information. Recent advances in statistical tools and identification of genetic markers informative for ancestry have enabled the genetic heterogeneity of populations to be described and applied to epidemiological studies. Genetic ancestry associations are a useful tool to suggest that a genetic component contributes to disease disparities and admixture mapping is implemented to identify genetic factors contributing to disease.37,38 Of importance is that genetic ancestry may be associated with socioeconomic factors.39–43 For example, Sánchez et al.42 revealed Amerindian ancestry was greater in individuals with fewer years of education. Complex associations among SES, ancestry, and lung cancer require examination to disentangle their contributions to lung cancer. We examined the relationship among SES, genetic ancestry, and lung cancer in a case–control study conducted with African Americans and Latinos.     

Socioeconomic Disparities in Community-Based Treatment of Tobacco Dependence

Objectives. We examined socioeconomic disparities in a community-based tobacco dependence treatment program.Methods. We provided cognitive-behavioral treatment and nicotine patches to 2739 smokers. We examined treatment use, clinical and environmental, and treatment outcome differences by socioeconomic status (SES). We used logistic regressions to model end-of-treatment and 3- and 6-month treatment outcomes.Results. The probability of abstinence 3 months after treatment was 55% greater for the highest-SES than for the lowest-SES (adjusted odds ratio [AOR] = 1.55; 95% confidence interval [CI] = 1.03, 2.33) smokers and increased to 2.5 times greater for the highest-SES than for the lowest-SES smokers 6 months after treatment (AOR = 2.47; 95% CI = 1.62, 3.77). Lower-SES participants received less treatment content and had fewer resources and environmental supports to manage a greater number of clinical and environmental challenges to abstinence.Conclusions. Targets for enhancing therapeutic approaches for lower socioeconomic groups should include efforts to ensure that lower-SES groups receive more treatment content, strategies to address specific clinical and environmental challenges associated with treatment outcomes for lower-SES smokers (i.e., higher dependence and stress levels and exposure to other smokers), and strategies to provide longer-term support.Tobacco use is a leading contributor to socioeconomic health disparities in the United States.1–5 Americans with household incomes of $15 000 or less smoke at nearly 3 times the rate of those with incomes of $50 000 or greater.6 Quit attempts show no socioeconomic gradient, but successful cessation is associated with a considerable socioeconomic disparity7–15 that appears to be increasing.4,16,17 Community-based tobacco dependence treatment programs can reduce these disparities by providing all smokers with needed assistance; however, smokers of lower socioeconomic status (SES) often have poorer treatment outcomes.18–23 Examination of factors related to socioeconomic disparities in treatment outcomes may identify targets for enhancing therapeutic approaches for lower-socioeconomic groups.In health research, SES is a broad construct describing relative access to basic resources required to achieve and maintain good health.24,25 Common measures of SES (e.g., educational achievement, income, occupation, wealth) assess different, albeit related aspects of the construct but are generally limited by a lack of precision and difficulty classifying all groups. Educational achievement is considered a basic element of SES, captures important aspects of lifestyle and behavior, and is perhaps the most widely used proxy for SES because of its influence on future occupational opportunities and earning potential; however, household income is considered the best measure of available material resources, especially for those who are not primary wage earners in families.24,26,27 Composite measures incorporate and, therefore, adjust for different aspects of SES.28In the United States, minority ethnic status often affects access to basic resources, but the magnitude of socioeconomic disparities is often greater than that between minority and majority ethnic groups in the United States, and the effects of minority ethnic status on smoking cessation are often reduced or eliminated after socioeconomic factors are taken into account.29–31 Nonetheless, in the United States, ethnic groups tend to live in different social and physical environments, and minority ethnic status often includes a constellation of stressors separate from and additive to SES.29 Moreover, lower SES coupled with tobacco use and minority ethnic status might lead to a unique set of multiple and cumulative disparities.29Conceptual models propose that health disparities emerge because of higher levels of stress, less access to physical and environmental resources, greater environmental constraints, fewer affective and cognitive resources, and poorer health behaviors.26,32 Consistent with these models, SES is empirically related to smoking cessation through complex reciprocal relations among numerous clinical and environmental factors, including stress, coping resources, psychological factors, exposure to other smokers, and use of treatment resources.33–38 Cognitive-behavioral treatment of tobacco dependence can potentially address many of these factors, but little is known about the role these factors play when lower-SES smokers are provided with treatment.Disparities are prominent among numerous factors important to cessation and treatment of tobacco dependence. In the United States, minority ethnic groups such as African Americans and Hispanic Americans as well as lower-SES groups are less likely to receive advice about and assistance with smoking cessation from health care providers.39–41 Although minority ethnic groups are no less likely to quit when provided with nicotine replacement,42 they and lower-SES groups are less likely to have accurate information about nicotine replacement and less likely to use evidence-based tobacco dependence treatments.43–47 Lower-SES groups are less likely to be covered by smoking bans in the workplace and at home,48–50 and some lower-SES groups are more highly nicotine dependent than higher-SES groups.51 The role of many of these disparities in the treatment of tobacco dependence remains relatively unexamined.We examined socioeconomic disparities in a community-based tobacco dependence treatment program in Arkansas. We used statistical modeling of treatment outcomes to examine the independent contributions of SES, ethnicity, and other factors. Consistent with conceptual models and previous studies, we hypothesized that the lowest-SES participants would have less treatment use and the greatest clinical and environmental challenges to achieving and maintaining abstinence from tobacco use.     

The Role of Socioeconomic Factors in Black–White Disparities in Preterm Birth

Objectives. We investigated the role of socioeconomic factors in Black–White disparities in preterm birth (PTB).Methods. We used the population-based California Maternal and Infant Health Assessment survey and birth certificate data on 10 400 US-born Black and White California residents who gave birth during 2003 to 2010 to examine rates and relative likelihoods of PTB among Black versus White women, with adjustment for multiple socioeconomic factors and covariables.Results. Greater socioeconomic advantage was generally associated with lower PTB rates among White but not Black women. There were no significant Black–White disparities within the most socioeconomically disadvantaged subgroups; Black–White disparities were seen only within more advantaged subgroups.Conclusions. Socioeconomic factors play an important but complex role in PTB disparities. The absence of Black–White disparities in PTB within certain socioeconomic subgroups, alongside substantial disparities within others, suggests that social factors moderate the disparity. Further research should explore social factors suggested by the literature—including life course socioeconomic experiences and racism-related stress, and the biological pathways through which they operate—as potential contributors to PTB among Black and White women with different levels of social advantage.Higher rates of preterm birth (PTB) among Blacks than Whites have been documented in the United States since at least the early 20th century.1–3 This racial disparity is of great concern because PTB strongly predicts infant mortality4,5 and adverse health and neurodevelopmental outcomes in childhood,4,6,7 and has been linked with chronic disease, disability, and premature mortality in adulthood.8–10The underlying reasons for the racial disparity in PTB are not well understood.4 A range of socioeconomic factors—including income, wealth, and education at the individual, household, and area levels—vary across racial/ethnic groups11–16 and are biologically plausible underlying causes of PTB.4,17–20 Socioeconomic effects on health, including PTB, could operate independently of and in concert with the effects of stressful experiences related more directly to racial discrimination.4,16,21,22 Many studies have observed different PTB risks associated with socioeconomic or socioeconomically linked characteristics of the geographic areas where women reside,4,11,23–32 including area-level measures of poverty, unemployment,26 segregation,24,28 and crime rates.25 Various individual-, household-, and neighborhood-level socioeconomic factors could plausibly affect PTB through diverse causal pathways, including those involving poor nutrition or prepregnancy health status, adverse health-related behaviors, lack of medical care, social isolation, stress, and hazardous physical exposures in the home, neighborhood, workplace, or in transit.4 Biological pathways leading from stressful experiences to PTB through neuroendocrine processes have been described.33–36A systematic review17 of studies examining relationships between adverse birth outcomes and socioeconomic factors found that 93 of 106 studies reported a significant association, overall or within a subgroup, between a socioeconomic measure and a birth outcome; effects varied, however, across racial/ethnic groups and socioeconomic measures. Several birth outcome studies have examined interactions between variables reflecting racial/ethnic group and socioeconomic factors, with inconsistent results. Some studies have found minimal or no Black–White differences in PTB among highly disadvantaged women.37–39 Others have observed a significant racial disparity among socioeconomically disadvantaged women, but an even greater disparity among more socioeconomically advantaged women.24,40,41 Some other studies, however, have not reported differences in the racial disparity in PTB across socioeconomic subgroups.4 Although the biological mechanisms for low birth weight are thought to be distinct from those for PTB,4 several studies42–49 have observed relatively smaller—but not necessarily small—racial disparities in low birth weight or infant mortality within socioeconomically disadvantaged versus more advantaged subgroups.In some studies, the Black–White disparity in PTB has persisted after adjustment for socioeconomic and other known or suspected risk factors,31,50–52 leading some researchers to conclude that the Black–White disparity in PTB reflects underlying genetic differences.53–56 Others have challenged this, noting that the disparity may reflect significant unmeasured socioeconomic factors and other social experiences including those related to racial discrimination throughout life, not only during pregnancy.18,21,57–62 With few exceptions,30,31,39,63,64 however, most studies of the Black–White disparity in PTB have had limited socioeconomic information, and few have examined systematically how the disparity may vary at different socioeconomic levels.The goal of this study was to investigate the role of socioeconomic factors in the Black–White disparity in PTB by using a unique population-based data source on California births with more extensive information than generally available in previous PTB research, including multiple socioeconomic measures at the individual, household, and area levels and a wide range of covariables reflecting potential confounders suggested by the literature. The aim was to assess the combined contribution of multiple socioeconomic factors—representing different dimensions of social advantage and disadvantage—to the racial disparity in PTB, and to examine whether and how these socioeconomic factors might moderate the relationship between racial group and PTB.     

Associations of acculturation and socioeconomic status with subclinical cardiovascular disease in the multi-ethnic study of atherosclerosis

Objectives. We assessed whether markers of acculturation (birthplace and number of US generations) and socioeconomic status (SES) are associated with markers of subclinical cardiovascular disease—carotid artery plaque, internal carotid intima-media thickness, and albuminuria—in 4 racial/ethnic groups.Methods. With data from the Multi-Ethnic Study of Atherosclerosis (n = 6716 participants aged 45–84 years) and race-specific binomial regression models, we computed prevalence ratios adjusted for demographics and traditional cardiovascular risk factors.Results. The adjusted US- to foreign-born prevalence ratio for carotid plaque was 1.20 (99% confidence interval [CI] = 0.97, 1.39) among Whites, 1.91 (99% CI = 0.94, 2.94) among Chinese, 1.62 (99% CI = 1.28, 2.06) among Blacks, and 1.23 (99% CI = 1.15, 1.31) among Hispanics. Greater carotid plaque prevalence was found among Whites, Blacks, and Hispanics with a greater number of generations with US residence (P < .001) and among Whites with less education and among Blacks with lower incomes. Similar associations were observed with intima-media thickness. There was also evidence of an inverse association between albuminuria and SES among Whites and Hispanics.Conclusions. Greater US acculturation and lower SES were associated with a higher prevalence of carotid plaque and greater intima-media thickness but not with albuminuria. Maintenance of healthful habits among recent immigrants should be encouraged.Beginning with the Ni-Hon-San study,^1,2 which was initiated in the 1960s, research has associated increased acculturation to Western lifestyles with more-adverse cardiovascular disease (CVD) risk factor profiles and with increased CVD morbidity and mortality. Specifically, greater Western acculturation has frequently been linked to increased body mass index (BMI; weight in kilograms divided by height in meters squared),^3–5 waist circumference and abdominal obesity,^6,7 hypertension,^7–9 type II diabetes,^10,11 and CVD morbidity and mortality.^1,12,13 However, little research has explored associations between acculturation and subclinical CVD.^14,15Abundant research also exists that links low socioeconomic status (SES) to increased levels of CVD risk factors, morbidity, and mortality.^14,16–18 In general, SES has been found to be inversely related to subclinical measures of CVD, including coronary artery calcification (CAC),^14,19–22 carotid artery plaque, and intima-media thickness^20,23–26 and albuminuria.²⁷ Relations with peripheral artery disease have been inconsistent.^28–30 The extent to which these associations vary by race/ethnicity has been examined infrequently. There is, however, some evidence that the relation between SES and disease may differ across racial/ethnic groups.^14,31,32 Specifically, in the Multi-Ethnic Study of Atherosclerosis (MESA) there was a higher prevalence of CAC among Whites with low education than among those with more education, whereas the reverse was true for Hispanics.¹⁴We investigated whether acculturation and SES were associated with other measures of subclinical disease, specifically with carotid plaque and albuminuria. The relation of acculturation and SES to CAC has been described in MESA.¹⁴ Although CAC, carotid plaque, and albuminuria are all subclinical measures of CVD and are related to adverse clinical outcomes, these measures represent different aspects of the disease process and have relatively weak intercorrelations.³³ Thus, they may be differentially related to our exposures of interest.The investigation of these patterns is important from a public health perspective and may yield clues regarding the etiology of atherosclerosis. On the basis of previous work,¹⁴ we hypothesized that increased Western acculturation, as assessed by place of birth, migration history, and duration of US residence, is associated with increased carotid plaque, intima-media thickness, and albuminuria. Additionally, we expected there to be an interaction between race/ethnicity and SES with respect to their associations with subclinical CVD. Specifically, we expected Whites and Blacks at lower SES to have more-adverse subclinical CVD profiles than those at higher SES, whereas for Hispanics and Chinese, we expected the reverse to be true.     

In-Person and Telephone Treatment of Tobacco Dependence: A Comparison of Treatment Outcomes and Participant Characteristics

Objectives. We compared participant characteristics and abstinence outcomes of smokers who chose in-person or telephone tobacco dependence treatment.Methods. We provided the same treatment content to 7267 smokers in Arkansas between 2005 and 2008 who self-selected treatment modality; examined demographic, clinical, environmental, and treatment utilization differences between modalities; and modeled outcomes and participants’ choice of modality with logistic regression.Results. At end of treatment, in-person participants were more likely to be abstinent than telephone participants, and smokers of higher socioeconomic status (SES) were more likely to be abstinent with telephone treatment than lower-SES smokers. Long term, modality had no effect on treatment outcomes. Higher-SES smokers and smokers exposed to more treatment content were more likely to achieve long-term abstinence, regardless of modality. Men and more recalcitrant smokers were more likely to choose in-person treatment; lower-SES, ethnic minority, and more dependent smokers were more likely to choose telephone treatment.Conclusions. Treatment modality attracts different groups of smokers, but has no effect on long-term abstinence. Multiple treatment modalities are needed to provide treatment to a heterogeneous population of smokers. More research is needed to understand the influences on treatment choice.Providing treatment of tobacco dependence is a vital component of comprehensive tobacco control programs.1 Cognitive–behavioral treatment (CBT) for tobacco dependence delivered through various modalities (in person and over the telephone) is well-validated2 and widely available in the United States, United Kingdom, and Canada, but there is a dearth of information about the comparative effectiveness among modalities especially in the context of providing treatment to a heterogeneous population of smokers in real-world settings.Because tobacco use is a leading contributor to socioeconomic health disparities, understanding the effects of socioeconomic status (SES) on treatment modality effectiveness as well as the choice of treatment modality is a priority.3–5 In the United States, those with household incomes of $15 000 or less smoke at nearly 3 times the rate of those with incomes of $50 000 or more.6 Although quit attempts demonstrate no socioeconomic gradient, successful cessation demonstrates a considerable socioeconomic disparity,7–10 which is broadening over time.5,11 In-person and telephone treatment modalities each have obvious strengths and limitations; however, it remains unclear how these modalities compare in terms of effectiveness for and their ability to attract lower-SES smokers.In-person CBT is the traditional behavioral treatment modality. Telephone CBT provided through proactive “quitlines” is a promising and practical innovation in treatment delivery.12,13 Proactive quitlines provide CBT to callers with scheduled contacts over several weeks, similar to in-person treatment. Quitlines are widely available in the United States, Canada, and the United Kingdom, albeit of varying types and intensities.13 Regardless of modality, CBT has a clear dose–response curve, with the most effective CBT including at least 4 contacts augmented with medication.2Telephone treatment is purported to be more desirable and accessible to lower-SES smokers than in-person treatment because it decreases logistical barriers to treatment, requiring less effort on the part of smokers,12 but there are little data to support this contention. In fact, some quitlines attract a greater proportion of higher-SES than lower-SES smokers, maintaining existing smoking-related socioeconomic disparities.14,15 Moreover, some lower-SES and ethnic minority smokers experience significant barriers to using proactive telephone treatment effectively (e.g., private access to a landline, available free cellular minutes, trust in a treatment provider located elsewhere).16 In addition, quitline promotion often uses extensive TV and radio media promotions13,17 that do not reach some lower-SES and ethnic minority communities.14,16 In-person treatment programs are purported to reach fewer smokers than telephone treatment because of geographic limitations18; however, they almost exclusively rely on less-extensive promotional methods (e.g., local word-of-mouth and health care provider referrals).7,19–22 These factors make it difficult to compare the ability of treatments to attract lower-SES smokers.The 2 existing comparisons between in-person and telephone treatment have significant limitations21,22; however, evidence suggests that smokers served by in-person and telephone programs have many similarities and differences. Both modalities attract urban and rural lower-SES smokers and, compared with the general population of smokers, a greater proportion of women.7,19–21,23–25 In-person participants are more likely to be older and more highly dependent21,22 and callers are more likely to be younger, more dependent, and more ready to quit22 than the general population of smokers. The most recent and most direct comparison between in-person and telephone treatment found no difference in treatment outcomes.21 The comparisons made in this study are limited, however, because the modalities offered different treatment content; there were systematic biases in treatment modality eligibility (e.g., insurance status, readiness to quit); and geographic proximity to in-person treatment was unaccounted for as were a wide range of demographic, clinical, environmental, and treatment utilization factors.21,22 Nonetheless, these findings suggest that each modality provides services for populations not reached by the other.21,22 To date, there are no direct comparisons of in-person and telephone treatments offering the same content and accounting for geographic proximity to in-person treatment as well as accounting for differences in participant demographic, clinical, environmental, and treatment utilization characteristics.From 2005 to 2008, the Arkansas state-funded tobacco dependence treatment program provided a unique opportunity to account for proximity to in-person treatment and directly compare in-person and telephone treatment outcomes and participant characteristics with the same treatment content delivered in both modalities. The large sample size, the extensive amount of data collected, and the heterogeneity of participants allowed us to account for demographic, clinical, environmental, and treatment utilization factors; proximity to in-person treatment; and the interaction between SES and treatment modality. We hypothesized that our results would support preliminary findings. We expected treatment modality to have no effect on treatment outcomes, and higher SES and increased treatment utilization to be associated with a greater likelihood of long-term abstinence. We expected both (modalities to attract a similarly large proportion of women, but telephone treatment to attract a higher proportion of lower-SES and ethnic minority smokers. We also expected smokers with higher dependence and greater motivation levels to be more likely to choose in-person treatment.     

Socioeconomic and ethnic differences in disease burden and disparities in physical function in older adults

Objectives. We investigated whether a greater burden of disease among poorer individuals and ethnic minorities accounted for socioeconomic and racial disparities in self-reported physical functioning among older adults.Methods. We used data from adults aged 60 years or older (n = 5556) in the Third National Health and Nutrition Examination Survey, 1988–1994 to test associations between education level, poverty index, and race/ethnicity and limitations in 11 functions. We adjusted for demographic features and measures of disease burden (comorbid conditions, smoking, hemoglobin level, serum albumin level, knee pain, body mass index, and skeletal muscle index).Results. Associations between education and functional limitations were attenuated after adjustment, but those with 0–8 years of education were more likely than those with 13 or more years of education to have limitations in 3 functions. Poverty was associated with a higher likelihood of limitations despite adjustment. The likelihood of limitations among non-Hispanic Blacks and Mexican Americans was similar to that of non-Hispanic Whites after adjustment.Conclusions. Socioeconomic disparities in functional limitations among older Americans exist independent of disease burden, whereas socioeconomic differences and disease burden account for racial disparities.Although the prevalence of disability among older adults in the United States has generally declined over the past decade, this trend has not extended to all segments of the population.^1–4 Disability among ethnic minorities and economically disadvantaged groups has not declined, resulting in widening ethnic and socioeconomic disparities.^5–11 Racial minorities and those who are economically disadvantaged are up to 3 times more likely to experience disability than are Whites and those who are not economically disadvantaged, respectively.^8,10,12,13 Achieving health equity has been a public policy priority, and collective interventions have been proposed.^12,14,15 Functional limitations in older adults are particularly important because of their prognostic and economic implications.¹⁶ Functional limitations predict further future decline in physical function,¹⁷ an increased risk of dementia,¹⁸ loss of independence, institutionalization, and mortality.^19–21According to the Institute of Medicine model of the enabling–disabling process, disability is a product of the complex interactions between a person and his or her psychological, social, and physical environments.²² In this context, functional limitations are partly a consequence of an individual''s burden of disease. Musculoskeletal conditions, chronic neurological and cardiopulmonary disorders, sensory and cognitive deficits, anemia, sarcopenia, and chronic pain may lead to functional limitations and disability. Many of the chronic health conditions that can affect physical functioning are more common among ethnic minorities and economically disadvantaged groups,^5,6,9–12 raising the question of whether a greater burden of disease can primarily explain the higher prevalence of functional limitations and disability in these groups.Previous studies of socioeconomic and ethnic disparities in functional limitations reported unadjusted data or data adjusted only for differences in demographic characteristics.^{10,11,23–27} Few studies have examined the role of differences in comorbid conditions, obesity, or smoking or simultaneously examined a range of indicators of disease burden.^6,9,28 We sought to determine whether socioeconomic and ethnic differences in functional limitations among noninstitutionalized older adults in the United States remain after adjusting for measures of disease burden.     

Effects of Different Types of Antismoking Ads on Reducing Disparities in Smoking Cessation Among Socioeconomic Subgroups

Objectives. We assessed which types of mass media messages might reduce disparities in smoking prevalence among disadvantaged population subgroups.Methods. We followed 1491 adult smokers over 24 months and related quitting status at follow-up to exposure to antismoking ads in the 2 years prior to the baseline assessment.Results. On average, smokers were exposed to more than 200 antismoking ads during the 2-year period, as estimated by televised gross ratings points (GRPs). The odds of having quit at follow-up increased by 11% with each 10 additional potential ad exposures (per 1000 points, odds ratio [OR] = 1.11; 95% confidence interval [CI] = 1.00, 1.23; P < .05). Greater exposure to ads that contained highly emotional elements or personal stories drove this effect (OR = 1.14; 95% CI 1.02, 1.29; P < .05), which was greater among respondents with low and mid-socioeconomic status than among high–socioeconomic status groups.Conclusions. Emotionally evocative ads and ads that contain personalized stories about the effects of smoking and quitting hold promise for efforts to promote smoking cessation and reduce socioeconomic disparities in smoking.Tobacco use inflicts the greatest burden of illness on those least able to afford it.^1,2 An enormous challenge for tobacco control is how to tackle the consistently higher levels of smoking prevalence found among disadvantaged groups,^3–5 especially because these gaps may be widening.^6,7 Televised antismoking campaigns provide an effective population-wide method of preventing smoking uptake,^8,9 promoting adult smoking cessation,¹⁰ and reducing adult smoking prevalence,¹¹ and research indicates that some types of ads may be more effective than others. Antismoking messages that produce strong emotional arousal, particularly personal stories or graphic portrayals of the health effects of smoking, tend to perform well¹²; they are perceived to be more effective than others, are more memorable, and generate more thought and discussion.^13–16 However, it is unclear whether different types of messages might maintain, increase, or mitigate the disparities in smoking prevalence across population subgroups.Research on subgroup differences in responses to a range of anti-tobacco ads has not found systematic differences by gender, race/ethnicity, or nationality.^13,17–19 A review of the literature on the use of mass media concluded that in comparison with their effects on other populations, campaigns have often been less effective, sometimes equally effective, but rarely more effective in promoting cessation among socioeconomically disadvantaged populations.²⁰ However, many of the less effective general-audience campaigns were hampered by minimal reach to smokers of low socioeconomic status (SES) because they were low-cost campaigns unable to afford extensive media exposure.²⁰Most research examining longer-term quit rates in the context of large-scale, well-funded antismoking campaigns found comparable quit rates or reductions in smoking prevalence in low- and high-SES groups.^21–28 However, to our knowledge, no population-based research has examined the relationship between the degree of exposure to different types of antismoking messages and quit rates between low- and high-SES groups.A variety of theories^29–38 provide guidance about which styles of ads may best encourage quitting, especially among members of lower socioeconomic groups. Consistent with these theories, reviews of the effects of antismoking advertising have concluded that advertisements that evoke strong emotional responses through negative visceral imagery or personal stories about the health effects of smoking can increase attention, generate greater recall and appeal, and influence smoking beliefs and intentions.^12,39,40 Recent research indicates that self-relevant emotional reactions (i.e., emotional reflections about one''s life, body, or behavior that are triggered by the ad⁴¹) may be especially persuasive, because they affect perceptions of future risk of becoming ill,⁴² which in turn have been linked with reduced cigarette consumption, increased intentions to quit, and quit attempts.⁴³Antismoking ads that use strong graphic imagery of the health effects of smoking are likely to be predominately associated with high negative emotional arousal, but personal stories of the consequences of smoking may evoke high or low levels of emotion depending on the particular story and the degree to which smokers relate to the characters.³⁸ However, less emotional personal testimonials may still be more effective than other types of less emotional ads because there is no explicit persuasive intent against which smokers may react^38,44 and because health information is presented in a story-based format, which people learn to process naturally from an early age.⁴⁵Because lower-SES groups tend to have a greater degree of resistance to messages from the health care sector,⁴⁶ lower health literacy levels,^47,48 greater likelihood of belief in myths about cancer risks and prevention,⁴⁹ and less perception that smoking increases a person''s chance of getting cancer,⁴⁸ we proposed that emotional messages and personal stories might be especially influential. Presenting antismoking messages in an emotional or personal testimonial format may convey health information to these smokers in a way that is difficult to discount, natural and easy to process, and likely to arouse emotions that lead to increased perceptions of susceptibility to smoking-related diseases and motivation to quit.^38,42,44Drawing on the only previous study to examine the effect on adult quitting of the degree of exposure to antismoking ads,¹⁰ we first hypothesized that when all types of advertisements were considered together, greater exposure to these antismoking ads would be associated with greater likelihood of quitting by follow-up. Our second hypothesis was that particular types of antismoking ads (those containing highly emotional elements or personal testimonials about the effects of smoking) would be associated with a greater chance of successful quitting by follow-up than would exposure to ads without these elements. Finally, we hypothesized that highly emotional or personal testimonial ads would be especially effective among lower-SES groups.     

Socioeconomic Disparities in Sleep Duration Among Veterans of the US Wars in Iraq and Afghanistan

We characterized socioeconomic disparities in short sleep duration, which is linked to multiple adverse health outcomes, in a population-based sample of veterans of the US wars in Iraq and Afghanistan who had interacted with the Minneapolis VA Health Care System. Lower reported household assets, lower food security, greater reported discrimination, and lower subjective social status were significantly (P < .05) related to less sleep, even after adjusting for demographics, health behaviors, and posttraumatic stress disorder diagnosis. Assisting veterans to navigate social and socioeconomic stressors could promote healthful sleep and overall health.Inadequate sleep is common, with just more than 1 in 4 adults in the United States reporting that they average 6 or less hours of sleep per night.1 Short sleep duration (commonly defined as < 6–8 hr per day) has been linked to serious health problems, including injury,2–4 cardiovascular disease and associated risk factors,5–14 poor mental health,15–19 and all-cause mortality.20–27 Disparities exist in which Blacks28–32 and those who are of lower socioeconomic status (SES)33 are at increased risk for sleep deficiency. Military members and veterans, especially those who have been deployed, appear to be at greater risk for short sleep duration.34–37 This risk may relate to aspects of the deployment cycle such as irregular schedule and shift work, stress, mental health issues such as posttraumatic stress disorder (PTSD), and injury. Of further concern is that short sleep duration and its risk factors may be part of a mutually reinforcing cycle. Indeed, research has indicated that predeployment short sleep duration may contribute to the development of PTSD.38,39In this study, we sought to characterize socioeconomic disparities in short sleep duration among veterans who served in the US wars in Iraq or Afghanistan and to test whether, independent of other known risk factors, socioeconomic obstacles, such as having low income or experiencing discrimination, are linked to short sleep duration.     

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).     

Life-Course Socioeconomic Position and Incidence of Diabetes Mellitus Among Blacks and Whites: The Alameda County Study, 1965�C1999

Objectives. We examined associations between several life-course socioeconomic position (SEP) measures (childhood SEP, education, income, occupation) and diabetes incidence from 1965 to 1999 in a sample of 5422 diabetes-free Black and White participants in the Alameda County Study.Methods. Race-specific Cox proportional hazard models estimated diabetes risk associated with each SEP measure. Demographic confounders (age, gender, marital status) and potential pathway components (physical inactivity, body composition, smoking, alcohol consumption, hypertension, depression, access to health care) were included as covariates.Results. Diabetes incidence was twice as high for Blacks as for Whites. Diabetes risk factors independently increased risk, but effect sizes were greater among Whites. Low childhood SEP elevated risk for both racial groups. Protective effects were suggested for low education and blue-collar occupation among Blacks, but these factors increased risk for Whites. Income was protective for Whites but not Blacks. Covariate adjustment had negligible effects on associations between each SEP measure and diabetes incidence for both racial groups.Conclusions. These findings suggest an important role for life-course SEP measures in determining risk of diabetes, regardless of race and after adjustment for factors that may confound or mediate these associations.Diabetes mellitus is a major cause of morbidity and mortality in the United States.^1,2 Type 2 diabetes disproportionately affects Hispanics, as well as non-Hispanic Black Americans, American Indians/Alaska Natives, and some Asian/Pacific Islander groups. In the United States, members of racial and ethnic minority groups are almost twice as likely to develop or have type 2 diabetes than are non-Hispanic Whites.^2–5 Significant racial and ethnic differences also exist in the rates of diabetes-related preventive services, quality of care, and disease outcomes.^6–10Researchers have attempted to determine why, relative to Whites, members of racial and ethnic minority groups are disproportionately affected by diabetes. For example, compared with White Americans, Black Americans are presumed to have stronger genetic^5,11 or physiological^11–13 susceptibility to diabetes, or greater frequency or intensity of known diabetes risk factors, such as obesity, physical inactivity, and hypertension.^14–17Black Americans also are more likely than are White Americans to occupy lower socioeconomic positions.¹⁸ Low socioeconomic position (SEP) across the life course is known to influence the prevalence^19–24 and incidence^3,19,25–30 of type 2 diabetes. The risk of diabetes also is greater for people who are obese,^3,17,31 physically inactive,^3,32 or have hypertension,^33,34 all of which are conditions more common among people with lower SEP.^16,35–37Several studies have focused on the extent to which socioeconomic factors, body composition (i.e., weight, height, body mass index, and waist circumference), and behaviors explain the excess risk of diabetes attributed to race.^4,12,19,30 For example, 2 separate studies, one with data from the Health and Retirement Study¹⁹ and the other with data from the Atherosclerosis Risk in Communities Study,³⁰ used race to predict diabetes incidence. Attempting to separate the direct and indirect effects of race on diabetes,³⁸ these studies assessed, via statistical adjustment, which socioeconomic measures and diabetes-related risk factors, when adjusted, could account for the excess risk among Black participants relative to White participants.^19,30 Adjustment for education lessened the effect of Black race on diabetes incidence in the Atherosclerosis Risk in Communities Study.³⁰ In the Health and Retirement Study, excess risk attributed to Black race was not explained by early-life socioeconomic disadvantage, but it was reduced after adjustment for education and later-life economic resources.¹⁹ The validity of this analytic approach has been challenged, however, because the socioeconomic measures used were assumed to have the same meaning across all racial/ethnic groups, a questionable assumption³⁸ in the United States, especially in 1965.We sought to explore the predictive effects of several life-course socioeconomic factors on the incidence of diabetes among both Black and White Americans. We examined demographic confounders (age, gender, marital status) and diabetes risk factors (obesity, large waist circumference, physical inactivity, high blood pressure, depression, access to health care) as possible mediators of the observed associations between SEP and incident diabetes (i.e., the development of new cases of diabetes over time).     

Differential Trends in Weight-Related Health Behaviors Among American Young Adults by Gender, Race/Ethnicity, and Socioeconomic Status: 1984�C2006

Objectives. We investigated temporal patterns from 1984 to 2006 in 6 weight-related health behaviors by using longitudinal data for multiple cohorts of young adults (aged 19–26 years) from the nationally representative Monitoring the Future Study.Methods. We used growth curve models to examine historical trends in 6 health behaviors: frequency of eating breakfast, eating green vegetables, eating fruit, exercising, watching television, and sleeping 7 hours each night. Variations across gender, race/ethnicity, and socioeconomic status were investigated.Results. Frequency of exercising was consistently lower among young adult women than young adult men over this 23-year period. Compared with White women, Hispanic women, and women from other race/ethnic groups, Black women showed declines in the frequency of exercise since 1984. In general, young adult women showed a marked increase in the frequency of eating breakfast over this period, although Black women did not show any net gains.Conclusions. Social disparities in body weight may increase because Black women, Hispanic women, and men with lower socioeconomic status show declining trends in positive weight-related health behaviors compared with White young adults with higher socioeconomic status.As the prevalence of obesity and overweight rises in the United States,^1–5 researchers continue to investigate a range of mechanisms by which people attain excessive body weight.^6–10 Agreement is growing that the source of the obesity epidemic lies in an environment that produces an energy gap,^11–15 where energy intake exceeds energy expenditure even by as little as 100 excess calories per day.^12,13 Yet, it is unclear whether this 100-calorie excess is a function of increased intake or decreased output (or some combination of both) in American activity and consumption behaviors over time.Limited data exist on trends in energy intake and energy expenditure among Americans over the past 3 decades, but the data that are available are nonetheless consistent with the rise in obesity observed over the same period. Between 1977 and 1996, Americans increased their total energy consumption by about 200 kcal/day.¹⁶ This was largely a result of increased consumption of snacks and soft drinks, particularly among young adults,^16,17 while vegetable and fruit consumption remained low.^18–21 These consumption behaviors have all been linked to excess weight gain.^22–25 The increased availability of inexpensive, energy-dense food and beverages^26–30 coupled with a lack of access to fresh fruits and vegetables^31,32 are some of the environmental factors that may contribute to these trends. The US population has also adopted an increasingly sedentary lifestyle^33–36 in an environment that is associated with a reduction in energy expenditure, including car-dependent neighborhoods that discourage walking and biking^37–41 and limited physical activity in schools.^28,42 On average, American youth spend over 30 hours per week watching television,⁴³ which is positively associated with being overweight, either through sedentary activity or through exposure to the marketing of poor-quality foods.^43–46 Modern lifestyles are increasingly characterized by skipping breakfast and sleeping less,^36,47–49 which have also been linked to energy imbalance.^50–56These reported trends in health behaviors, however, are based on data from repeated cross-sectional surveys^18,21,57 that were often conducted up to 5 years or more apart,^16,21,57 the results of which are typically reported in aggregate across a time span of 4 to 7 years.^20,57 Moreover, published articles frequently focus on trends in only 1 health behavior (e.g., fruit and vegetable consumption^18,20) and not the relative practice of energy consumption and expenditure behaviors among individuals over time. As a result, more detailed trends in health behaviors, particularly as they illustrate subtle changes in the balance of energy intake and output occurring annually among American young adults over the last quarter century, are poorly understood.Also, differences in these behaviors and their trends by gender, socioeconomic status (SES), and racial/ethnic background are not well described at a population level, even though well-documented health disparities in obesity by social position exist.^4,58–61 Using data from the National Health and Nutrition Examination Survey (1988–2002), one study found that non-Hispanic Blacks, persons in poverty, and those with less than a high school education were less likely to meet US Department of Agriculture fruit and vegetable guidelines than were non-Hispanic Whites and socioeconomically advantaged individuals.⁵⁷ However, these results were based on 2 cross-sectional data sets collected 5 years apart. Delva et al.¹⁰ used repeat cross-sectional data collected annually from secondary school students between 1986 and 2003 to report declining trends in the proportion of adolescents who ate breakfast or exercised regularly, with a lower prevalence among women, racial/ethnic minorities, and those with low SES. Trends in the frequency of these behaviors beyond the secondary school setting, however, remain largely undocumented.The purpose of our study was, first, to investigate long-term patterns in weight-related health behaviors among young adults (aged 19–26 years) over the past 23 years (1984–2006) and, second, to assess how these patterns varied by social position (race/ethnicity, gender, and SES). Analyses were based on longitudinal data for multiple cohorts of individuals with frequent repeat measures to better track historical changes in weight-related health behaviors over time. By focusing on young adults, we aimed to better understand how weight-related health behaviors have changed in this early period of the adult life course, when many adult health behavior patterns show their formative roots. The transition to adulthood (sometimes referred to as emerging or early adulthood) is a period when individuals are on their own typically for the first time, when life plans are put into action, and when distinctive life paths become more manifest.⁶² We hypothesized that the frequency of healthy behaviors would generally decline among young adults over this period, and that the rate of decline would be greater among those in disadvantaged social positions (women, Blacks, Hispanics, and those of lower SES).     

Socioeconomic and Racial/Ethnic Disparities in the Incidence of Bacteremic Pneumonia Among US Adults

Objectives. We examined associations between the socioeconomic characteristics of census tracts and racial/ethnic disparities in the incidence of bacteremic community-acquired pneumonia among US adults.Methods. We analyzed data on 4870 adults aged 18 years or older with community-acquired bacteremic pneumonia identified through active, population-based surveillance in 9 states and geocoded to census tract of residence. We used data from the 2000 US Census to calculate incidence by age, race/ethnicity, and census tract characteristics and Poisson regression to estimate rate ratios (RRs) and 95% confidence intervals (CIs).Results. During 2003 to 2004, the average annual incidence of bacteremic pneumonia was 24.2 episodes per 100 000 Black adults versus 10.1 per 100 000 White adults (RR = 2.40; 95% CI = 2.24, 2.57). Incidence among Black residents of census tracts with 20% or more of persons in poverty (most impoverished) was 4.4 times the incidence among White residents of census tracts with less than 5% of persons in poverty (least impoverished). Racial disparities in incidence were reduced but remained significant in models that controlled for age, census tract poverty level, and state.Conclusions. Adults living in impoverished census tracts are at increased risk of bacteremic pneumonia and should be targeted for prevention efforts.Bacterial pneumonia is an important cause of morbidity and mortality in adults¹ and is a potentially serious complication of influenza infection.^2,3 Racial/ethnic disparities in the incidence of bacterial pneumonia are a public health problem. Among US adults, rates of bacteremic pneumonia caused by Streptococcus pneumoniae (pneumococcus), the leading cause of community-acquired pneumonia, are higher among Blacks than among Whites.⁴ Vaccination against pneumococcal disease is recommended for persons aged 65 years and older, for cigarette smokers, and for persons with certain chronic conditions.⁵ Vaccination coverage with 23-valent pneumococcal polysaccharide vaccine is lower, however, among Hispanic and non-Hispanic Black adults with indications for vaccination than among non-Hispanic White adults.^6,7 The introduction of pneumococcal conjugate vaccination for children in 2000 led to lower pneumococcal disease incidence in all age groups^8,9 and narrowed the difference between incidence in Black and White children, although disparities persist among adults.^10,11 Less is known about the factors influencing racial/ethnic disparities in the incidence of bacteremic pneumonia caused by other common pathogens. A better understanding of the underlying factors that sustain disparities in bacterial disease would help to direct prevention efforts.Several previous studies examined the contributions of socioeconomic inequalities to racial/ethnic disparities in invasive pneumococcal disease.^12–15 Between 1960 and 1970, a series of population-based studies in US communities identified socioeconomic measures, including average income and education, as strongly associated with both race/ethnicity and bacterial meningitis incidence.^16–18 However, socioeconomic data have not routinely been collected in US surveillance systems for invasive bacterial disease. With geocoding software, individual cases can be mapped to census tract of residence.¹⁵ Census tract–level socioeconomic measures can then be included in analyses of health outcomes to better understand racial/ethnic disparities in disease incidence.¹⁹ We used a large population-based surveillance system for invasive bacterial infections to examine associations between the socioeconomic characteristics of census tracts and racial/ethnic disparities in the incidence of bacteremic community-acquired pneumonia among US adults. We sought to identify a single, publicly available census tract characteristic that could be used to target interventions to geographic areas likely to have high incidences of bacteremic pneumonia and to monitor inequalities in disease burden.     

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.     

Social gradients in oral health in older adults: findings from the English longitudinal survey of aging

Objectives. We examined prospective associations between socioeconomic position (SEP) markers and oral health outcomes in a national sample of older adults in England.Methods. Data were from the English Longitudinal Survey of Aging, a national cohort study of community-dwelling people aged 50 years and older. SEP markers (education, occupation, household income, household wealth, subjective social status, and childhood SEP) and sociodemographic confounders (age, gender, and marital status) were from wave 1. We collected 3 self-reported oral health outcomes at wave 3: having natural teeth (dentate vs edentate), self-rated oral health, and oral impacts on daily life. Using multivariate logistic regression models, we estimated associations between each SEP indicator and each oral health outcome, adjusted for confounders.Results. Irrespective of SEP marker, there were inverse graded associations between SEP and edentulousness, with proportionately more edentate participants at each lower SEP level. Lower SEP was also associated with worse self-rated oral health and oral impacts among dentate, but not among edentate, participants.Conclusions. There are consistent and clear social gradients in the oral health of older adults in England, with disparities evident throughout the SEP hierarchy.The inverse linear relationship between socioeconomic position (SEP) and health is well established.^1–4 The uneven distribution of health across socioeconomic strata has been observed in both industrialized and less developed countries and for most common diseases and causes of death.^1,5–8 In most cases, the association between SEP and health is characterized by a linear graded pattern, with people in each lower SEP category having successively worse levels of health and dying earlier than those that are better off, a characteristic known as the social gradient in health.⁹Although there is clear and consistent evidence about the existence of the social gradient in working-age adults,^10,11 studies in older adults are less consistent, with some showing attenuation of the gradient^12,13 and others reporting that it persisted^14,15 or even increased¹⁶ in magnitude.Oral health is particularly important at older ages with tooth loss shown to be independently associated with disability and mortality.^17–20 Oral health status in older people is also an important determinant of nutritional status.²¹Socioeconomic disparities in oral health have been consistently demonstrated for various indicators, mostly clinical and disease related^22–31 but also subjective measures of oral health and quality of life.^30,32–38 Some of these studies have explicitly assessed the existence of an oral health gradient,^{23,25–31,34–37} but almost all were carried out on adolescents and adults, with very few focusing on older people.^33,36 These few relevant studies are cross-sectional and inconclusive and have used a limited number of SEP indicators (typically, education and occupational class), thereby hindering any comprehensive analysis on the relationship between SEP and oral health.We addressed the gap in the literature about the existence of an oral health gradient at older ages by examining the prospective associations between a wide range of SEP indicators (education, occupation, household income, household wealth, subjective social status [SSS], and childhood SEP) and various oral health outcomes (presence of natural teeth, self-rated oral health, and oral impacts) in a national sample of older adults from the English Longitudinal Survey of Aging (ELSA). We explored whether there are any significant socioeconomic inequalities in oral health among older people in England and, if so, whether these take the form of a gradient.     

The Relation Between Health Insurance and Health Care Disparities Among Adults With Disabilities

Objectives. We examined disparities among US adults with disabilities and the degree to which health insurance attenuates disparities by race, ethnicity, and socioeconomic status (SES).Methods. We pooled data from the 2001–2007 Medical Expenditure Panel Survey on individuals with disabilities aged 18 to 64 years. We modeled measures of access and use as functions of predisposing, enabling, need, and contextual factors. We then included health insurance and examined the extent to which it reduced observed differences by race, ethnicity, and SES.Results. We found evidence of disparities in access and use among adults with disabilities. Adjusting for health insurance reduced these disparities most consistently for emergency department use. Uninsured individuals experienced substantially poorer access across most measures, including reporting a usual source of care and experiencing delays in or being unable to obtain care.Conclusions. Although health insurance is an important enabling resource among adults with disabilities, its effect on reducing differences by race, ethnicity, and SES on health care access and use was limited. Research exploring the effects of factors such as patient–provider interactions is warranted.Continuing its emphasis on reductions in health care disparities, Healthy People 2020 identifies the elimination of health disparities as 1 of 4 overarching goals.1 Congress has charged the Agency for Healthcare Research and Quality (AHRQ) with tracking disparities in health care access and quality among racial, ethnic, and socioeconomic groups, as well as for priority populations. In April 2012, AHRQ released its ninth report, finding that, although there was evidence of improvements in quality of care, health care access and quality are suboptimal, particularly for individuals who are racial/ethnic minorities or of lower socioeconomic status (SES).2An estimated 1 in 5 noninstitutionalized individuals in the United States experiences a disability.3 Although individuals with disabilities have been identified as a priority population by Congress,2 examining disparities among those with disabilities has garnered less attention. There is evidence that individuals with disabilities receive fewer preventive and treatment services than individuals without disabilities.4–7 Individuals with disabilities are more likely to report cost as a barrier to care,4,8 to report higher out-of-pocket costs,9 and to report unmet need for medical care.8Individuals with disabilities are disproportionately racial/ethnic minority and of lower SES. Rates of disability are higher for Blacks (22.2%) than for Hispanics (17.8%) and Whites (17.4%).3 Using data from the American Community Survey, Erickson and Lee10 found prevalence of disability to decline with increasing income. Disability is also associated with educational attainment. Substantially more people without a disability (30.8%) had a bachelor’s degree or higher than people with a disability (12.5%). Limited work has focused on disparities by race and SES on health care access and use among individuals with disabilities.11Health insurance provides an essential link to health services and outcomes,12,13 attenuating but not eliminating disparities by race and SES in the general population.14 Data from the 2010 American Community Survey indicate that, nationally, 82.1% of working-age individuals with disabilities had health insurance, compared with 78.2% among working-age individuals without disabilities.15 Nationally, 17.9% of working-age adults with disabilities were uninsured, but there was substantial state variability. Adults with disabilities are much more likely to have public, relative to private, coverage—50.5% public and 43% private coverage nationally in 2010 (some individuals have both public and private coverage). Research has rarely examined the extent to which health insurance coverage reduces potential disparities by race, ethnicity, and SES among individuals with disabilities. Thus, we extended the research on disparities among individuals with disabilities by examining whether minority and lower-SES adults with disabilities experience disparate access to and use of health care services.     

Education associations with smoking and leisure-time physical inactivity among Hispanic and Asian young adults

Objectives. We assessed whether associations between education and 2 health behaviors—smoking and leisure-time physical inactivity (LTPI)—depended on nativity and age at immigration among Hispanic and Asian young adults.Methods. Data came from the 2000–2008 National Health Interview Survey. The sample included 13 345 Hispanics and 2528 Asians aged 18 to 30 years. Variables for smoking and LTPI were based on self-reported data. We used logistic regression to examine education differentials in these behaviors by nativity and age at immigration.Results. The association of education with both smoking and LTPI was weaker for foreign-born Hispanics than for US-born Hispanics but did not vary by nativity for Asians. Education associations for smoking and LTPI among foreign-born Hispanics who had immigrated at an early age more closely resembled those of US-born Hispanics than did education associations among foreign-born Hispanics who had immigrated at an older age. A similar pattern for smoking was evident among Asians.Conclusions. Health-promotion efforts aimed at reducing disparities in key health behaviors among Hispanic and Asian young adults should take into account country of residence in childhood and adolescence as well as nativity.An extensive literature has established the existence of a social gradient in health, whereby health improves with each increment in socioeconomic status (SES).^1,2 Although most health outcomes show social gradients, research has increasingly suggested that SES may not have the same effect on health for all US populations.^3–6 In particular, researchers have found more modest socioeconomic differentials in health outcomes and related health behaviors for foreign-born populations than for corresponding US-born populations.^4,5,7One explanation for this pattern proposes that weaker social gradients in health and health behaviors among the foreign-born are rooted in lifestyle-related norms and practices in sending countries for US immigration, which may continue to shape outcomes along socioeconomic lines after arrival.⁴ We sought to extend the research in this area by assessing whether the relationship between education and some health behaviors depends not only on nativity but also on country of residence during childhood and adolescence. Although a recent study found that the association between subjective social status and mood dysfunction among Asian immigrants varied by age at immigration,⁶ to our knowledge no research has examined patterns for objective measures of SES and health behaviors. The results of this analysis may improve understanding of differences between social gradients in health behaviors in US populations and may inform efforts to target interventions to groups at higher risk for unhealthy practices.Our conceptual framework is informed by several areas of research. Numerous studies suggest that some health behaviors, such as smoking, are heavily influenced by early life experiences.^8–10 In addition, disparities in some health behaviors begin to form in childhood and adolescence, both within and outside the United States.^10–13 Mechanisms that shape health behaviors by SES (e.g., access to and affordability of unhealthy lifestyles among individuals with lower versus higher SES, variation in norms and sanctions surrounding particular practices by SES) may operate differently in the sending countries for US immigration. Finally, research on acculturation suggests that as immigrants enter new contexts, their health behaviors shift toward patterns observed among native-born populations, a process that may be especially influential during childhood and adolescence.^14–17 Although these changes may affect immigrants across the socioeconomic spectrum, they may also vary by SES if young immigrants adopt the health behaviors of native-born youths with similar socioeconomic backgrounds.We focused our analysis on education gradients in smoking and leisure-time physical inactivity (LTPI). The identification of consistencies in the influence of education, nativity, and age at immigration across health behaviors may inform a more comprehensive approach to addressing disparities. We selected these behaviors for study because of their associations with education and nativity and because both are shaped in part by mechanisms operating during childhood and adolescence.^11,18–20 Additionally, smoking and physical inactivity are among the leading actual causes of death in the United States.²¹We examined associations between these health behaviors and education, rather than income or occupational status, because education may better represent SES for individuals who do not work consistently in the paid workforce, an issue that is particularly relevant for immigrant populations.^5,22,23 Education also provides an indicator of the family socioeconomic environment during childhood and adolescence. We focused on young adults (aged 18–30 years) partly because of limitations on data available to determine age at immigration (explained in detail in the Methods section). However, patterns in young adulthood may provide insights into patterns for related health outcomes in older populations.We first determined whether differences in education gradients in smoking and LTPI by nativity (documented for adults of all ages) were evident among young adults.^4,5 If education gradients in smoking and LTPI are influenced by exposures in early life, then variation by nativity should be evident by young adulthood. Second, and more important, we investigated whether associations between education and both smoking and LTPI among foreign-born young adults who immigrated in childhood or adolescence more closely resembled associations among the US-born than was the case for the foreign-born who immigrated after adolescence. We focused on Hispanics and Asians because these groups include large immigrant populations. Finally, we assessed whether patterns varied by Hispanic and Asian subgroup and by gender.     

Disentangling the Influence of Socioeconomic Status on Differences Between African American and White Women in Unmet Medical Needs

Objectives. We sought to disentangle the relationships between race/ethnicity, socioeconomic status (SES), and unmet medical care needs.Methods. Data from the 2003–2004 Community Tracking Study Household Survey were used to examine associations between unmet medical needs and SES among African American and White women.Results. No significant racial/ethnic differences in unmet medical needs (24.8% of Whites, 25.9% of African Americans; P = .59) were detected in bivariate analyses. However, among women with 12 years of education or less, African Americans were less likely than were Whites to report unmet needs (odds ratio [OR] = 0.57; 95% confidence interval [CI] = 0.42, 0.79). Relative to African American women with 12 years of education or less, the odds of unmet needs were 1.69 (95% CI = 1.24, 2.31) and 2.18 (95% CI = 1.25, 3.82) among African American women with 13 to 15 years of education and 16 years of education or more, respectively. In contrast, the relationship between educational level and unmet needs was nonsignificant among White women.Conclusions. Among African American women, the failure to recognize unmet medical needs is related to educational attainment and may be an important driver of health disparities, representing a fruitful area for future interventions.African Americans are more likely than Whites to have unmet medical care needs according to objective clinical standards such as burden of disease (e.g., higher rates of heart disease and cancer deaths), clinical symptoms of ill health, and preventable hospitalizations.^1,2 Unmet medical need, considered a critical indicator of lack of access to care, is also commonly assessed through subjective indices such as self-reported ability to obtain needed medical care or postponing of needed medical care.^3,4 Studies based on these subjective measures often reveal that African Americans report less need for medical care than Whites,^5–7 but this finding has not been consistent.^8–10 In any event, such a finding suggests that subjective measures capture personal perceptions of need for care rather than (or in addition to) true clinical need.^3,4,11Complex and poorly studied factors influence the link between true medical needs and perceived medical needs, especially among members of racial/ethnic minority groups. Theoretical and empirical research has underscored the limitations of subjective measures of medical need. Signs and symptoms of disease may be a better proxy for unmet medical needs among vulnerable populations.^1,11–14 For example, Cunningham and Hadley¹¹ recently showed that, among members of racial/ethnic minority groups, symptom-specific measures of unmet need were more accurate than general measures.In the United States, race/ethnicity, socioeconomic status (SES), and health have been historically intertwined.¹⁵ SES (e.g., education, occupation, and income) accounts for a large portion of the health disparities observed between members of racial/ethnic minority groups and members of more advantaged groups.^15,16 Also, SES may partly account for differences in how illness severity and risk are perceived. Individuals of low SES, especially members of racial/ethnic minority groups, are more likely than individuals of high SES to underestimate illness severity and the need of medical care for serious conditions such as cancer, stroke, and obesity.^17–21 African Americans and all individuals with low incomes are more likely to underestimate their risk for heart attack, stroke, and cancer than are their counterparts and are less likely to use screening programs and seek appropriate care.^22,23 Thus, perceptions of medical need among members of racial/ethnic minority groups are strongly linked to SES.²⁴Although the literature clearly documents strong links between race/ethnicity, SES, and medical need, the overall picture is not clear. Nationally representative studies with detailed adjustment for SES among specific demographic populations are not available. More specifically, women are more likely than are men to delay or not obtain needed medical care,^25,26 and their unmet needs are more likely to result in mortality.²⁷ The relationship between SES and health may be critically shaped by gender.²⁸ For example, lower SES is associated with poorer health, and, in general, women have lower levels of education than men.^29,30 However, little has been done to disentangle the complex interrelationships among race/ethnicity, SES, and perceptions of unmet or delayed need, especially among women.In an attempt to fill this important gap, we used data from a nationally representative, community-based survey of African American and White women to examine how race/ethnicity and SES are associated with perceived unmet medical care needs. More specifically, we attempted to answer the following question: how does SES influence the relationship between race/ethnicity and perceptions of unmet or delayed need for care among women? Our study was guided by the King and Williams²⁴ conceptual framework for understanding racial differences in health. According to that framework,

race is a proxy variable representing how biological, cultural, socioeconomic, sociopolitical, and discrimination factors … jointly influence health practices, psychosocial and environmental stress, medical care, and ultimately health outcomes.^24(p107)

     

Neighborhood socioeconomic status and influenza hospitalizations among children: New Haven County, Connecticut, 2003-2010

Objectives. We examined surveillance data for disparities in pediatric influenza-associated hospitalizations according to neighborhood socioeconomic status (SES) measures in New Haven County, Connecticut.Methods. We geocoded influenza-associated hospitalization case data from the past 7 years for children from birth to age 17 years and linked these to US Census 2000 tract-level SES data. Following the methods of Harvard''s Public Health Disparities Geocoding Project, we examined neighborhood SES variables, including measures of poverty and crowding. We calculated influenza-associated hospitalization incidence by influenza season and individual case characteristics, stratified by SES measures.Results. Overall, the mean annual incidence of pediatric influenza-associated hospitalization in high-poverty and high-crowding census tracts was at least 3 times greater than that in low-poverty and low-crowding tracts. This disparity could not be fully explained by prevalence of underlying conditions or receipt of influenza vaccination.Conclusions. Linkage of geocoded surveillance data and census information allows for ongoing monitoring of SES correlates of health and may help target interventions. Our analysis indicates a correlation between residence in impoverished or crowded neighborhoods and incidence of influenza-associated hospitalization among children in Connecticut.In the United States, influenza is a frequent cause of hospitalization for young children. Recent surveillance data indicate that the burden of pediatric influenza-associated hospitalization is between 10 and 30 cases per 100 000 population.¹ Many well-established risk factors exist for influenza complications in children, including age younger than 6 months, asthma, and other underlying medical conditions.² However, insufficient data exist on the relationship between socioeconomic status (SES) and severe influenza infections in children.Few communicable disease surveillance systems currently capture individual SES data. In lieu of individual-level SES information, US Census data can be used to describe the socioeconomic conditions of the neighborhood in which an individual lives. Neighborhood affects health independently of personal socioeconomic and behavioral characteristics.^3–5 Moreover, studies have shown the value of geocoding and linking surveillance data to US Census data in describing the epidemiology of infectious and noninfectious diseases.^6–8Using population-based surveillance data from the Connecticut Emerging Infections Program, we investigated potential disparities in pediatric influenza-associated hospitalizations according to neighborhood SES measures.