Neighborhood SES Research Articles

Abstract 3434: Neighborhood obesogenic environment and the risk of prostate cancer: The Multiethnic Cohort

Abstract Background: Obesity is a potentially modifiable risk factor for advanced prostate cancer (PCa). However, the role of the neighborhood obesogenic environment, characterized by obesity-related built and social environment measures, has not been evaluated in relation to PCa risk. Objective: To examine the association of neighborhood obesogenic environment with PCa risk in African American (AA), Japanese American (JA), Latino (LA), and White (WH) men in the California component of the Multiethnic Cohort (MEC) Study. Method: Individual-level sociodemographic data and health behaviors were linked with neighborhood measures of built and social environment for 42,850 men in the MEC, who predominately live in Los Angeles County. A principal components factor analysis was used to create indices based on 10 measures—neighborhood SES, population density, total businesses, recreational facilities, retail food environment, restaurant environment, parks, street connectivity, commuting by car, and traffic density—resulting in 4 obesogenic environment indices: physically active, low SES urban, businesses density, and unhealthy food. During a mean follow-up of 15 years and through linkage to the California Cancer Registry, 4,775 incident PCa cases were identified. Multivariable Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations between each index and PCa risk, overall and stratified by race/ethnicity and disease aggressiveness. For Latinos, additional stratified analyses were conducted by nativity. Results: Associations between the obesogenic indices and PCa risk varied by race/ethnicity. WH residing in low business environments experienced lower PCa risk (quintile [Q] 1 [low] vs. Q5 [high]: HR, 0.56 [95% CI, 0.41-0.77], p-trend: 0.0002). Among AA, unhealthy food environments were associated with greater risk of aggressive disease (advance stage or Gleason score > = 7) (more vs. no: HR, 1.36 [95% CI, 1.09-1.70], p-trend: 0.0026). Among LA, living in Hispanic enclaves was associated with reduced risk (Q3-5 [high] vs. Q1-2 [low]: HR, 0.86 [95% CI, 0.75-0.98]), but living in high business environments was associated with increased risk of PCa (Q1 [low] vs. Q5 [high]: HR, 1.35 [95% CI, 1.05-1.73], p-trend: 0.0002) for those born in the US (p-trend: 0.0059). Lower SES urban environments were associated with a decreased risk of non-aggressive disease among LA (Q5 [low] vs. Q1 [high]: HR, 0.78 [95% CI, 0.63-0.98], p-trend: 0.0026), and was more marked among foreign-born (p trend = 0.0074) than US-born (p trend = 0.1211). Conclusions: Built and social environment factors are associated with PCa risk, but their associations varied by race/ethnicity, nativity (among LA), and disease aggressiveness. An unhealthy food environment was strongly associated with the risk of aggressive prostate cancer in AA men, warranting further investigation into the underlying mechanisms. Citation Format: Li Tao, Scarlett L. Gomez, Salma Shariff-Marco, Juan Yang, Song Yi Park, Cheryl Albright, Kristine Monroe, Brian Henderson, Laurence Kolonel, Loic Le Marchand, Lynne Wilkens, Iona Cheng. Neighborhood obesogenic environment and the risk of prostate cancer: The Multiethnic Cohort. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3434.

Associations between neighborhood socioeconomic environment and physical activity in Cuban immigrants

Physical inactivity is a major public health concern because it is a determinant of obesity and obesity-related chronic diseases. Few longitudinal studies have examined the association between neighborhood socioeconomic (SES) environment and change in physical activity behaviors. Additionally, few studies have examined this association in immigrant groups or Hispanic subgroups such as Cubans. This research aimed to determine if neighborhood SES is associated with longitudinal change in moderate-to-vigorous physical activity (MVPA) among Cuban immigrants who participate in the Cuban Health Study in Miami, Florida. Data on 280 participants [mean age: 37.4 (±4.6), 48.9% women, mean body mass index: 25.0 (±2.5)] collected at baseline, 12 months and 24 months were analyzed. Minutes of MVPA were objectively measured during each data collection period using accelerometers. A neighborhood SES score was calculated for each participant’s residential census tract from American Community Survey data on median household income, median housing value, educational attainment and occupation. The neighborhood SES score was grouped into tertiles, reflecting low, moderate and high neighborhood SES environment. Multilevel linear models were used to examine the relationship between neighborhood SES and change in MVPA over 24 months. At baseline, 94 (33.6%), 108 (38.6%) and 78 (27.9%) participants resided in low, moderate, and high SES neighborhoods, respectively. After adjusting for age, sex, and body mass index, no difference in average change in MVPA over time was observed between participants residing in low and moderate SES neighborhoods (p=0.48) or low and high SES neighborhoods (p=0.62). In Cuban immigrants, longitudinal change in MVPA may not vary by neighborhood socioeconomic environment.

Combined effect of individual and neighborhood socioeconomic status on mortality in patients with newly diagnosed dyslipidemia: A nationwide Korean cohort study from 2002 to 2013

Background and AimThe study aims to determine whether dyslipidemia patients living in less affluent neighborhood are at a higher risk of mortality compared to those living in more affluent neighborhoods. Methods and resultsA population-based cohort study was conducted using a stratified representative sampling from the National Health Insurance claim data from 2002 to 2013. The target subjects comprise patients newly diagnosed with dyslipidemia receiving medication. We performed a survival analysis using the Cox proportional hazard model.Of 11,946 patients with dyslipidemia, 1053 (8.8%) subjects died during the follow-up period. Of the dyslipidemia patients earning a middle-class income, the adjusted HR in less affluent neighborhoods was higher than that in the more affluent neighborhoods compared to the reference category of high individual SES in more affluent neighborhoods (less affluent; hazard ratio (HR) = 1.64, 95% confidence interval (CI): 1.35–1.99 vs. more affluent; HR = 1.48, 95% CI: 1.20–1.81, respectively). We obtained consistent results in patients with lower income, wherein the adjusted HR in less affluent neighborhoods was higher than that in more affluent neighborhoods (less affluent; HR = 1.52, 95% CI: 1.16–1.97 vs. more affluent; HR = 1.41, 95% CI: 1.04–1.92, respectively). ConclusionLiving in a less affluent neighborhood contributes to higher mortality among dyslipidemia patients. The individual- and neighborhood-level variables cumulatively affect individuals such that the most at-risk individuals include those having both individual- and neighborhood-level risk factors. These findings raise important clinical and public health concerns and indicate that neighborhood SES approaches should be essentially considered in health-care policies similar to individual SES.

Abstract A67: Do hospital characteristics explain racial/ethnic disparities in mortality after breast cancer diagnosis: The California Breast Cancer Survivorship Consortium

Abstract Introduction: Disparities in breast cancer mortality persist between racial/ethnic groups. Little is known about the role of the treatment environment, specifically the characteristics of the hospital reporting a patient's breast cancer diagnosis. Differential access to high quality care contributes to disparities in treatment and outcomes. The California Breast Cancer Survivorship Consortium (CBCSC) integrated data on patient demographics, behavioral and reproductive characteristics from patient interviews, and on tumor characteristics, treatment, and follow-up from the California Cancer Registry. This study leveraged the large size and racial/ethnic diversity to examine the extent to which hospital characteristics explain racial/ethnic disparities in mortality following breast cancer diagnosis. Methods: Using data from five of the six studies in the CBCSC, the study sample included 4,624 non-Latina whites, 1,849 Latinas, 1,832 African-Americans, and 1,333 Asian Americans diagnosed with Stage I-IV breast cancer between 1993 and 2007. We used study- and stage-stratified Cox regression models to assess the independent associations of hospital characteristics with mortality, and examined the change in racial/ethnic hazard ratios before and after adjustment for hospital characteristics. Hospital characteristics included composition measures based on the patients served by each hospital such as SES (percent of cancer patients from the highest quintile SES neighborhoods), race/ethnicity, and insurance type as well as NCI cancer center designation. Distance from patients' residences to hospitals was also examined. Patient sociodemographics include race/ethnicity, education, marital status, and neighborhood SES; behavioral and reproductive factors include smoking, alcohol consumption, obesity, exercise, family history of breast cancer, and parity; and clinical factors include tumor characteristics, treatment, and co-morbidities. Results: For all-cause mortality, patients seen in high SES hospitals had lower mortality rates than those seen in low SES hospitals (HR=0.87, 95% CI=0.75-0.99). The other hospital characteristics were not associated with all-cause mortality. Compared with non-Latina whites, we observed a higher mortality rate for African-Americans (HR=1.40, 95% CI=1.23-1.58), a lower mortality rate for Latinas (HR=0.89, 95% CI=0.78-1.01) and no statistically different rate for Asian Americans (HR=0.80, 95% CI=0.60-1.07). After adjusting for hospital characteristics, the higher mortality rate observed for African-Americans was slightly attenuated (HR=1.34, 95% CI= 1.18-1.51) whereas the lower mortality rate for Latinas became slightly stronger (HR=0.86, 95% CI=0.75-0.98). No statistically significant associations were observed for breast cancer-specific mortality. We also tested for interactions between race/ethnicity and hospital characteristics and found no statistically significant interactions. Conclusion: Hospital SES (as measured based on patient composition) is independently associated with all-cause mortality after a diagnosis of breast cancer, even after adjusting for a patient's educational level and neighborhood SES. However, adjusting for hospital characteristics accounted only slightly for the higher overall mortality rate among African-Americans and strengthened the lower mortality rate observed among Latinas. The fact that most breast cancer treatment occurs outside of hospitals may explain the lack of an observed association with disease-specific mortality; by contrast, hospital SES likely signifies a combination of factors (for example, the presence and severity of co-morbidities beyond what was measured, and access to effective care) that contribute to a gradient in all-cause mortality. Citation Format: Salma Shariff-Marco, Allison W. Kurian, Juan Yang, Jocelyn Koo, Esther M. John, Theresa H. M. Keegan, Iona Cheng, Kristine R. Monroe, Cheryl Vigen, Marilyn L. Kwan, Yani Lu, Brian E. Henderson, Leslie Bernstein, Richard Sposto, Anna H. Wu, Scarlett L. Gomez. Do hospital characteristics explain racial/ethnic disparities in mortality after breast cancer diagnosis: The California Breast Cancer Survivorship Consortium. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr A67.

Abstract B25: Impact of neighborhood obesogenic factors on obesity in over 100,000 participants of the Multiethnic Cohort Study

Abstract Introduction: The obesity epidemic is a serious health priority with important consequences on obesity-associated cancers. Socioeconomic (SES) and “obesogenic” attributes of neighborhoods may promote obesity by providing a context where it is difficult to engage in physical activity and/or access healthy foods. This may be particularly relevant for minority populations that have limited neighborhood resources and experience higher levels of obesity. However, the extent to which these neighborhood factors translate into individual levels of body mass index (BMI) have been mixed among racial/ethnic groups. Therefore, leveraging the scale and racial/ethnic diversity of the Multiethnic Cohort (MEC) study, we examined the associations between neighborhood obesogenic factors and BMI among African Americans, Japanese Americans, Latinos, and Whites in California. Methods: Study subjects included 107,697 MEC participants, ages 45-75, residing in California (93% from Los Angeles County) with geocoded addresses and data available on BMI at baseline questionnaire (1993-1996). Residential baseline addresses were geocoded to latitude and longitude coordinates and assigned to 1990 Census block groups to ascertain neighborhood levels of SES, population density, and commute patterns. In addition, geocodes were linked to business data to quantify neighborhood attributes of the retail/restaurant food environment, parks, recreational facilities, walkability, traffic density, and total businesses within a residential buffer area of one mile in radius. Polytomous logistic regression was conducted to examine the relationship between the obesogenic environment and BMI in kg/m2 (underweight: BMI<18.5; normal weight: BMI=18.5-<25 (reference); overweight BMI=25-<30; obese BMI>30) adjusting for age, sex, and race/ethnicity and including all neighborhood obesogenic factors. Stratified analyses were conducted by gender and race/ethnicity. Results: Lower neighborhood SES was significantly associated with higher odds of being overweight and obese. For males, in comparison to the highest SES quintile (Q5), the odds ratios and 95% confidence intervals for obesity with decreasing SES quintiles were Q4: OR=1.36 (95% CI: 1.20-1.50), Q3: OR=1.59; (95% CI: 1.40-1.81), Q2: OR=1.70 (95% CI: 1.49-1.93), and Q1: OR=1.89 (95% CI: 1.63-2.19). For females, similar patterns of associations were seen although larger associations were observed (Q4: OR=1.52 (95% CI: 1.36-1.70), Q3: OR=2.11 (95% CI: 1.89-2.34), Q2: OR=2.72 (95% CI: 2.43-3.03), Q1: OR=3.34 (95% CI: 2.94-3.78)). All racial/ethnic groups demonstrated similar patterns of associations between SES and obesity. Neighborhoods with smaller density of businesses (i.e. fewer nearby walkable destinations) were significantly associated with higher odds of obesity (ORQ1 vs. Q5=1.24; 95% CI: 1.14-1.34). This association was consistently observed among African American males and females, U.S. born Latino males, foreign-born Latino females, and White females. For White males and females, residence in neighborhoods with lower levels of commuting by car or motorcycle were associated with lower odds of obesity in comparison to residence in neighborhoods at the highest level of commuting by car or motorcycle (males ORQ1 vs. Q5=0.51; 95% CI: 0.35-0.76; females ORQ1 vs. Q5=0.64; 95% CI: 0.48-0.84). Conclusion: These findings demonstrate the impact of the neighborhood environment on obesity with complex relationships observed across gender and racial/ethnic groups. Future analyses will incorporate individual-level health behaviors such as dietary factors, physical activity and smoking, as well estimates of genetic ancestry. Our understanding of this relationship between the obesogenic environment and obesity provides a framework for future studies of neighborhood obesogenic factors and cancer risk. Citation Format: Iona Cheng, Juan Yang, Andrew Hertz, Christina Clarke, Cheryl Albright, Loic Le Marchand, Laurence Kolonel, Brian Henderson, Kristine Monroe, Scarlett Lin-Gomez, Lynne Wilkens. Impact of neighborhood obesogenic factors on obesity in over 100,000 participants of the Multiethnic Cohort Study. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr B25.

Fast food price, diet behavior, and cardiometabolic health: Differential associations by neighborhood SES and neighborhood fast food restaurant availability in the CARDIA study

Little research has addressed whether neighborhood context influences associations between fast food price, diet, and cardiometabolic health. We investigated these associations using 25 years of Coronary Artery Risk Development in Young Adults (CARDIA) study data (n=4,469, observations=21,134). We found a negative association between fast food price and consumption, with stronger inverse associations in more (vs. less) deprived neighborhoods [3rd tertile: β=−0.68 (95% CI: (−0.85, −0.51); 1st tertile: β=−0.22 (95% CI: −0.42, −0.02); p-interaction-0.002], and a similar association for BMI [3rd tertile: β=−1.34 (95% CI: −1.54, −1.14); 1st tertile: β=−0.45 (95% CI: −0.66, −0.25); p-interaction<0.001], but not insulin resistance [3rd tertile: β=−0.07 (95% CI: −0.24, 0.09); 1st tertile: β=0.09 (95% CI: −0.08, 0.26); p-interaction=0.40]. We observed no modification of fast food price by fast food availability. Future research on obesity disparities should consider potential differences in the association between fast food prices and health outcomes across neighborhood socioeconomic levels.

Abstract 885: Lower mortality among married cancer patients: How much of the effect is explained by socioeconomic and health insurance status

Abstract Background: Cancer patients who are married at diagnosis have lower mortality than the unmarried. Although this effect has been attributed to increased social support among married patients, whether economic resources influence this association remains unclear. Purpose: We assessed whether overall mortality differences between married and unmarried cancer patients is modified by neighborhood socioeconomic status (nSES) and mediated by health insurance status. Methods: We studied patients newly diagnosed (first invasive primary) with one of the 10 most common causes of cancer deaths from 2000 through 2009 in California. Information on patient nSES (based on block-group- level Census 2000 or 2007-2011 American Community Survey data), insurance (primary and secondary payer source), demographic and tumor characteristics, and follow-up through 2012 were obtained from the California Cancer Registry. Using Cox proportional hazards regression, we estimated overall mortality [hazard ratio (HR)] associated with marital status among N = 377,932 males (194,216 deaths) and N = 378,447 females (175,414 deaths), stratified on stage and adjusting for age, race/ethnicity, cancer site, nSES, insurance status, and treatment. Results: Prior to adjustment for insurance status, unmarried patients had higher overall mortality than married patients [HR (males) = 1.28 (1.27-1.29), HR (females) = 1.20 (1.19-1.21)]. This association was marginally stronger among patients from higher SES neighborhoods [HR (males) = 1.30 (1.28-1.32), HR (females) = 1.21 (1.20-1.23)] than from lower SES neighborhoods [HR (males) = 1.27 (1.26-1.29), HR (females) = 1.19 (1.18-1.21)] and only slightly lower after adjustment for insurance status. The magnitude of the associations varied by race/ethnicity and cancer site, with the largest marital status effect sizes seen for: high SES non-Hispanic White males with non-Hodgkin lymphoma [1.62 (1.52-1.73)], low SES Black males with pancreatic cancer [1.40 (1.20-1.63)], high SES Hispanic males with prostate cancer [1.50 (1.33-1.69)], high SES Asian males with pancreatic cancer [1.57 (1.28-1.92)], high SES non-Hispanic White females with breast cancer [1.34 (1.29-1.38)] or NHL [1.34 (1.24-1.44)], low SES Black females with NHL [1.43 (1.13-1.81)], and high SES Hispanic [1.44 (1.12-1.86)] and Asian [1.59 (1.24-2.05)] females with leukemia. The largest attenuation of HRs after adjustment for insurance was seen among Blacks, regardless of nSES [males: from 1.26 (1.22-1.30) to 1.20 (1.16-1.24), females: from 1.15 (1.11-1.20) to 1.10 (1.06-1.15)]. Conclusions: Neighborhood SES and insurance status had no considerable impact on the association between marital status and mortality after cancer diagnosis. Citation Format: Scarlett L. Gomez, Alison Canchola, Susan Hurley, Christina A. Clarke, Iona Cheng, Theresa H. M. Keegan, Sally L. Glaser, Maria Elena Martinez. Lower mortality among married cancer patients: How much of the effect is explained by socioeconomic and health insurance status. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 885. doi:10.1158/1538-7445.AM2015-885

Intersection of Race/Ethnicity and Socioeconomic Status in Mortality After Breast Cancer.

We investigated social disparities in breast cancer (BC) mortality, leveraging data from the California Breast Cancer Survivorship Consortium. The associations of race/ethnicity, education, and neighborhood SES (nSES) with all-cause and BC-specific mortality were assessed among 9372 women with BC (diagnosed 1993-2007 in California with follow-up through 2010) from four racial/ethnic groups [African American, Asian American, Latina, and non-Latina (NL) White] using Cox proportional hazards models. Compared to NL White women with high-education/high-nSES, higher all-cause mortality was observed among NL White women with high-education/low-nSES [hazard ratio (HR) (95 % confidence interval) 1.24 (1.08-1.43)], and African American women with low-nSES, regardless of education [high education HR 1.24 (1.03-1.49); low-education HR 1.19 (0.99-1.44)]. Latina women with low-education/high-nSES had lower all-cause mortality [HR 0.70 (0.54-0.90)] and non-significant lower mortality was observed for Asian American women, regardless of their education and nSES. Similar patterns were seen for BC-specific mortality. Individual- and neighborhood-level measures of SES interact with race/ethnicity to impact mortality after BC diagnosis. Considering the joint impacts of these social factors may offer insights to understanding inequalities by multiple social determinants of health.

Looking Beyond Income and Education: Socioeconomic Status Gradients Among Future High-Cost Users of Health Care.

Healthcare spending occurs disproportionately among a very small portion of the population. Research on these high-cost users (HCUs) of health care has been overwhelmingly cross-sectional in nature and limited to the few sociodemographic and clinical characteristics available in health administrative databases. This study is the first to bridge this knowledge gap by applying a population health lens to HCUs. We investigate associations between a broad range of SES characteristics and future HCUs. A cohort of adults from two cycles of large, nationally representative health surveys conducted in 2003 and 2005 was linked to population-based health administrative databases from a universal healthcare plan for Ontario, Canada. Comprehensive person-centered estimates of annual healthcare spending were calculated for the subsequent 5 years following interview. Baseline HCUs (top 5%) were excluded and healthcare spending for non-HCUs was analyzed. Adjusted for predisposition and need factors, the odds of future HCU status (over 5 years) were estimated according to various individual, household, and neighborhood SES factors. Analyses were conducted in 2014. Low income (personal and household); less than post-secondary education; and living in high-dependency neighborhoods greatly increased the odds of future HCUs. After adjustment, future HCU status was most strongly associated with food insecurity, personal income, and non-homeownership. Living in highly deprived or low ethnic concentration neighborhoods also increased the odds of becoming an HCU. Findings suggest that addressing social determinants of health, such as food and housing security, may be important components of interventions aiming to improve health outcomes and reduce costs.

Neighborhood deprivation and warfarin, aspirin and statin prescription — A cohort study of men and women treated for atrial fibrillation in Swedish primary care

BackgroundWe aimed to study differences in the prescribing of warfarin, aspirin and statins to patients with atrial fibrillation (AF) in socio-economically diverse neighborhoods. We also aimed to explore the effects of neighborhood deprivation on the relationship between CHADS2 risk score and warfarin prescription. MethodsData were obtained from primary health care records that contained individual clinical data that were linked to national data on neighborhood of residence and a deprivation index for different neighborhoods. Logistic regression was used to estimate the potential neighborhood differences in prescribed warfarin, aspirin and statins, and the association between the CHADS2 score and prescribed warfarin treatment, in neighborhoods with high, middle (referent) and low socio-economic (SES). ResultsAfter adjustment for age, socio-economic factors, co-morbidities and moves to neighborhoods with different SES during follow-up, adults with AF living in high SES neighborhoods were more often prescribed warfarin (men odds ratio (OR) (95% confidence interval (CI): 1.44 (1.27–1.62); and women OR (95% CI): 1.19 (1.05–1.36)) and statins (men OR (95% CI): 1.23 (1.07–1.41); women OR (95% CI): 1.23 (1.05–1.44)) compared to their counterparts residing in middle SES. Prescription of aspirin was lower in men from high SES neighborhoods (OR (95% CI): 0.75 (0.65–0.86)) than in those from middle SES neighborhoods. Higher CHADS2 risk scores were associated with higher warfarin prescription which remained after adjustment for neighborhood SES. ConclusionsThe apparent inequalities in pharmacotherapy seen in the present study call for resource allocation to primary care in neighborhoods with low and middle socio-economic status.

Worksite neighborhood and obesogenic behaviors: findings among employees in the Promoting Activity and Changes in Eating (PACE) trial.

Understanding mechanisms linking neighborhood context to health behaviors may provide targets for increasing lifestyle intervention effectiveness. Although associations between home neighborhood and obesogenic behaviors have been studied, less is known about the role of worksite neighborhood. To evaluate associations between worksite neighborhood context at baseline (2006) and change in obesogenic behaviors of adult employees at follow-up (2007-2009) in a worksite randomized trial to prevent weight gain. Worksite property values were used as an indicator of worksite neighborhood SES (NSES). Worksite neighborhood built environment attributes associated with walkability were evaluated as explanatory factors in relationships among worksite NSES, diet, and physical activity behaviors of employees. Behavioral data were collected at baseline (2005-2007) and follow-up (2007-2009). Multilevel linear and logistic models were constructed adjusting for covariates and accounting for clustering within worksites. Product-of-coefficients methods were used to assess mediation. Analyses were performed after study completion (2011-2012). Higher worksite NSES was associated with more walking (OR=1.16, 95% CI=1.03, 1.30, p=0.01). Higher density of residential units surrounding worksites was associated with more walking and eating five or more daily servings of fruits and vegetables, independent of worksite NSES. Residential density partially explained relationships among worksite NSES, fruit and vegetable consumption, and walking. Worksite neighborhood context may influence employees' obesogenic behaviors. Furthermore, residential density around worksites could be an indicator of access to dietary and physical activity-related infrastructure in urban areas. This may be important given the popularity of worksites as venues for obesity prevention efforts.

Do the effects of adolescent employment differ by employment intensity and neighborhood context?

Research on the effects of adolescent employment on primarily middle-class youth suggests that intense employment, working more than 15 or 20 hours during the school year, is associated with increased participation in risky behavior. Despite these findings, scholars who focus on the development of youth living in low-income urban areas often hypothesize that adolescent employment will have beneficial effects on this population. There is some evidence that adolescent employment is associated with increased educational achievement and adult employment for low-income urban youth. The impact of adolescent employment on future engagement in risky behavior across levels of neighborhood deprivation and employment intensity was investigated on a sample of 1,057 adolescents from the Project on Human Development in Chicago Neighborhoods, a longitudinal study of neighborhood effects on development. After controlling for individual characteristics, intense employment during adolescence did predict increased use of cigarettes and alcohol and having a greater number of sexual partners 2years after employment was measured. There were no significant interactions between neighborhood SES and adolescent employment status on involvement in risky behavior. These findings suggest that intense adolescent employment is associated with detrimental developmental outcomes for youth regardless neighborhood context.

Is socioeconomic status associated with utilization of health care services in a single-payer universal health care system?

ObjectivesTo assess an association of Socio-economic status with utilization of health care services between years 2002 and 2008 in Israel.MethodsWe retrospectively analyzed the utilization of health care services in a cohort of 100,000 members, 21 years and older, of a Clalit Health Services. The research compared utilization according to the neighborhood SES status; and clinic’s location as another SES proxy. Data included: Charlson Score morbidity factor, utilization of health care services (visits to primary physicians and specialists, purchase of pharmaceuticals, number of hospitalization days, visits to ED, utilization of laboratory tests and imaging). The analysis was performed using Generalized Linear Model (GLM) technique.ResultsPeople with lower SES visited more the ED and primary physicians and were hospitalized for longer periods. People with higher SES visited more specialists, bought more prescription drugs and used more medical imaging. The associations between SES and most of the services we analyzed did not change between 2002 and 2008. However, the gap between lower and higher SES levels in ED visits and the use of prescription drugs slightly increased over time, while the gap in visits to specialists decreased.ConclusionsThe research shows that even in a universal health care system SES is associated with utilization of health care services. In order to improve equity in utilization of services the Israeli public health should reduce economic barriers and in parallel invest in making information accessible to improve “navigation skills” for all.

Abstract 4137: Latent class model characterization of neighborhood SES

Abstract Background: Breast cancer is the most common cancer in women and a significant source of mortality. Neighborhood-level socioeconomic status (NSES) has been shown to play a key role in health; poorer health outcomes are observed in deprived neighborhoods even after controlling for individual level SES. Commonly used NSES indexes are difficult to interpret. The relative impact of different factors within the index cannot be evaluated. Latent class models, which use latent variables to create distinct classes, allow for characterization of NSES and estimation of the effects of specific neighborhood characteristics on cancer outcomes. Methods: We used data from women diagnosed with breast cancer from a teaching hospital in Philadelphia, PA. Census information at the Zip Code Tabulation Area (ZCTA) level was used to obtain NSES variables. Latent class analysis and comparisons of model fit statistics were used to determine the optimal number of classes. Results: Complete ZCTA-level data was available for 1,664 breast cancer patients. In this population, NSES was best represented by two separate latent variables, each with 2-classes (LC2). When the class variables were compared to a continuous NSES index (NSI), the correlation was 0.85. However, LC2 demonstrated stronger association with race, stage, disease subtype, tumor size, and histologic grade. Conclusions: We classified neighborhoods based on correlated socioeconomic census-level variables. Latent variables identify specific characteristics associated with living in a neighborhood with low versus high advantage and disadvantage and thus may improve our understanding of critical breast cancer prognostic factors and the targeting of cancer control efforts. Further research will provide overall structural latent models that incorporate information on tumor biology, prognostic variables and survival outcomes to aid in the identification of vulnerable populations. Table 1. Neighborhood latent class model (LC2) and SES Index (NSI) Table 1.Neighborhood latent class model (LC2) and SES Index (NSI)LC2 *ModelNSI Model *Prognostic Factor Stage24.5511.61 Race366.44331.01 Subtype18.4315.48 Size22.532.91* Chi-square statistic for association of Prognostic Factor with LC2 class or with NSI quartile. Higher number indicates higher strength of association. Citation Format: Aimee Palumbo, Yvonne Michael, Terry Hyslop. Latent class model characterization of neighborhood SES. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4137. doi:10.1158/1538-7445.AM2014-4137

The association between objective walkability, neighborhood socio-economic status, and physical activity in Belgian children.

BackgroundObjective walkability is an important correlate of adults’ physical activity. Studies investigating the relation between walkability and children’s physical activity are scarce. However, in order to develop effective environmental interventions, a profound investigation of this relation is needed in all age groups. The aim of this study was to investigate the association between objective walkability and different domains of children’s physical activity, and to investigate the moderating effect of neighborhood socio-economic status in this relation.MethodsData were collected between December 2011 and May 2013 as part of the Belgian Environmental Physical Activity Study in children. Children (9–12 years old; n = 606) were recruited from 18 elementary schools in Ghent (Belgium). Children together with one of their parents completed the Flemish Physical Activity Questionnaire and wore an accelerometer for 7 consecutive days. Children’s neighborhood walkability was calculated using geographical information systems. Multilevel cross-classified modeling was used to determine the relationship between children’s PA and objectively measured walkability and the moderating effect of neighborhood SES in this relation.ResultsIn low SES neighborhoods walkability was positively related to walking for transportation during leisure time (β = 0.381 ± 0.124; 95% CI = 0.138, 0.624) and was negatively related to sports during leisure time (β = −0.245 ± 0.121; 95% CI = −0.482, −0.008). In high socio-economic status neighborhoods, walkability was unrelated to children’s physical activity. No relations of neighborhood walkability and neighborhood socio-economic status with cycling during leisure time, active commuting to school and objectively measured moderate- to vigorous-intensity physical activity were found.ConclusionsNo univocal relation between neighborhood walkability and physical activity was found in 9–12 year old children. Results from international adult studies cannot be generalized to children. There is a need in future research to determine the key environmental correlates of children’s physical activity.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-014-0104-1) contains supplementary material, which is available to authorized users.

Commentary: race and sex are causes.

Commentary: race and sex are causes.

Neighborhood and Geographic Factors Associated with Diagnostic Resolution After an Abnormal Breast or Cervical Cancer Screening Test Among Women Enrolled in a Patient Navigator Program

Abstract This study's aim was to assess the associations between neighborhood and geographic factors and diagnostic resolution within 12 months following an abnormal screening test for breast or cervical cancer among participants of the Ohio Patient Navigator Research Program. Methods: Patient (demographic, psychosocial, and socioeconomic status [SES]) and neighborhood (SES, racial segregation, healthcare access) factors of 776 women attending one of 16 clinics and living in one of 285 census tracts in greater Columbus, Ohio were examined. Women were randomized at the clinic level to determine receipt of the navigation intervention. Multilevel logistic regression was used to estimate associations between these factors and diagnostic resolution while controlling for clinic and neighborhood clustering. Spatial analysis assessed the presence of geographic disparities (i.e., regions of significantly high odds of not resolving). Results: After adjustment for individual-level SES and the receipt of the clinic-level navigation intervention, there was a significant inverse association between neighborhood-level percent of residents without a bachelor's degree and odds of diagnostic resolution (odds ratio = 0.79, 95% confidence interval = 0.63–0.98). Adjustment for neighborhood percent of residents without a bachelor's degree accounted for geographic disparities in diagnostic resolution. Racial segregation, home-to-clinic distance and PN were not associated with odds of resolution. Conclusions: Women were more likely to have diagnostically resolved 12 months following an abnormal breast or cervical cancer screening test if they lived in neighborhoods of higher SES. Geographic disparities in diagnostic resolution could be reduced if there was no variation in neighborhood SES.

Economic Adversity and Depressive Symptoms in Mothers: Do Marital Status and Perceived Social Support Matter?

Over the past decade there has been increasing interest in the idea that marriage and perhaps other forms of interpersonal support can buffer the negative effects of poverty. The current study tests the hypothesis that marital status, perceived social support and neighborhood collective efficacy can moderate the effects of economic adversity on depressive symptoms among parents. Hierarchical Linear Modeling was used to analyze data from the Project on Human Development in Chicago Neighborhoods. Participants were 1,957 mothers of minor children. Analysis of main effects revealed associations between neighborhood SES (β = −0.69, SE (0.15), p < .001), family income (β = −0.11, SE (0.05), p = .02) financial strain (β = 0.51, SE (0.18), p = .004), being single (β = 0.63, SE (0.24), p = .009) and perceived social support (β = −0.22, SE (0.03), p < .001) on depressive symptoms. The hypothesis that interpersonal resources can buffer the effects of economic adversity was not supported. There were no significant interactions between marital status and economic adversity. There was a significant interaction between perceived social support and neighborhood level socioeconomic status (β = −0.07, SE (0.03), p = .04) but the effects of social support were weakest in neighborhoods characterized by low socioeconomic status.

Longitudinal Influences of Neighbourhood Built and Social Environment on Children’s Weight Status

The objective was to examine longitudinal 4-year-relationships between neighbourhood social environment and children’s body mass index-standard deviation score (BMI-SDS) taking into account the built environment. Furthermore, we have analysed the influence of potential interactions between the social environment and family/social data on children’s BMI-SDS. Between 2006–2008 and 2010–2012, anthropometric measurements were conducted among 485 children (age at baseline: 6.1 (5.8–6.4)). Socio-demographic characteristics and perception of residential environment were reported by parents. Geographic Information Systems were used to examine street length, number of food outlets and distance to the nearest playground and park/green space within an 800 m Euclidian buffer of each participant address point. Additional data on neighbourhood characteristics (e.g., traffic density, walkability, crime rates) were obtained from the State Capital of Kiel, Germany. In a multivariate model, walkability, street type, socioeconomic status of the district and perceived frequency of passing trucks/busses were associated with BMI-SDS over 4 years, but only neighbourhood SES had an effect on change in BMI-SDS. However, familial/social factors rather than neighbourhood environment (especially social environment) had an impact on children’s BMI-SDS over 4 years. Thus, social inequalities in childhood overweight are only partially explained by social neighbourhood environment.

Neighborhood socioeconomic status and substance use by U.S. adults

BackgroundThis study examined relationships of extremes in neighborhood socioeconomic status with use of tobacco, alcohol, marijuana and other drugs. Hypotheses were (1) residence in disadvantaged neighborhoods would be positively associated with stress-related and higher-risk substance use patterns (e.g., drug use), and (2) residence in affluent neighborhoods would be positively associated with “healthy” substance use (e.g., drinking within recommended guidelines) and negatively associated with substance use patterns incompatible with a culture of health. Age was examined as a potential moderator. MethodsData were from nationally-representative samples of U.S. adults (N=14,531) from the 2000 and 2005 National Alcohol Surveys linked with indicators of neighborhood SES from the 2000 U.S. Decennial Census. Analyses included gender-stratified multivariate logistic regression using weights to adjust for sampling and non-response. ResultsAs hypothesized, compared to middle-class neighborhoods, residence in disadvantaged neighborhoods was associated with higher odds of both men's and women's tobacco use and with women's other drug use. Residence in affluent neighborhoods was associated with lower odds of men's tobacco use and women's marijuana use. The association of neighborhood SES with men's tobacco use was modified by age, with the highest odds of daily tobacco use evident for all men in disadvantaged neighborhoods, as well as for younger men in middle-class neighborhoods. There were no significant associations of either alcohol outcome with neighborhood SES. ConclusionsIncreased risk of substance use for younger residents in both disadvantaged and middle-class neighborhoods and for older residents in disadvantaged neighborhoods suggest a need for targeted prevention interventions.