Previous findings have linked lower socioeconomic status (SES) with elevated morbidity and mortality. Leukocyte telomere length (LTL), which also has been associated with age-related disease morbidity and mortality, is a marker of aging at the cellular level, making it a valuable early biomarker of risk and an indicator of biological age. It is hypothesized that SES will be associated with LTL, indicating that SES influences disease risk by accelerating biological aging. In the present sample we test for associations of childhood SES and adult SES (i.e. education, income, home ownership) with LTL, and examine whether these associations vary by racial/ethnic group. Analyses on 963 subjects (18.7% White, 53% Hispanics, and 28.5% African American) from the Stress ancillary study of the Multi-Ethnic Study of Atherosclerosis revealed a significant difference in LTL between home owners and renters in Hispanic and White participants (p < .05), but not amongst African Americans (p = .98). There were no linear associations of adult education or family income with LTL, however, there was an inverse association between father’s education and LTL (p = .03). These findings suggest that for Whites and Hispanics renting vs. owning a home is associated with an older biological age; however we did not replicate previous findings linking education with LTL.
Telomere length; childhood SES; socioeconomic status; home ownership; wealth; parental education; cellular aging; biological aging; ethnicity
The primary goal was to test the hypothesis that limited social support (SS) is related to shorter leukocyte telomere length (LTL), particularly in an older adult population.
Cross-sectional analyses were performed on 948 participants at Exam 1 of the Multi-Ethnic Study of Atherosclerosis (MESA), ages 45–84 years (18.4% White, 53.1% Hispanics, and 28.5% African-American). LTL was determined using qPCR and social support was measured with the ENRICHD social support inventory.
Across the entire sample, SS was not associated with LTL (p = .87) after adjusting for demographic (age, gender, race/ethnicity, socioeconomic status), age X gender, age X race, health (body mass index, diabetes, pulse pressure), and lifestyle factors (smoking, physical activity, diet), however the interaction term Age (dichotomized) X SS was significant, p = .001. Stratification by age group revealed a positive association between SS (score range: 5–25) and LTL in the older (65–84 years) B(SE) = .005(.002), p = .007, but not younger participants (45–64 years), p = .12, after adjusting for covariates.
These results from a racially/ethnically diverse community sample of men and women provide initial evidence that low SS is associated with shorter LTL in adults aged 65 and older and is consistent with the hypothesis that social environment may contribute to rates of cellular aging, particularly in late life.
telomere length; social support; cellular aging; loneliness; isolation; older adults
Previous studies on the relationship of neighborhood disadvantage with alcohol use or misuse have often controlled for individual characteristics on the causal pathway, such as income—thus potentially underestimating the relationship between disadvantage and alcohol consumption.
We used data from the Coronary Artery Risk Development in Young Adults study of 5115 adults aged 18–30 years at baseline and interviewed 7 times between 1985 and 2006. We estimated marginal structural models using inverse probability-of-treatment and censoring weights to assess the association between point-in-time/cumulative exposure to neighborhood poverty (proportion of census tract residents living in poverty) and alcohol use/binging, after accounting for time-dependent confounders including income, education, and occupation.
The log-normal model was used to estimate treatment weights while accounting for highly-skewed continuous neighborhood poverty data. In the weighted model, a one-unit increase in neighborhood poverty at the prior examination was associated with a 86% increase in the odds of binging (OR = 1.86 [95% confidence interval = 1.14–3.03]); the estimate from a standard generalized-estimating-equations model controlling for baseline and time-varying covariates was 1.47 (0.96–2.25). The inverse probability-of-treatment and censoring weighted estimate of the relative increase in the number of weekly drinks in the past year associated with cumulative neighborhood poverty was 1.53 (1.02–2.27); the estimate from a standard model was 1.16 (0.83–1.62).
Cumulative and point-in-time measures of neighborhood poverty are important predictors of alcohol consumption. Estimators that more closely approximate a causal effect of neighborhood poverty on alcohol provided a stronger estimate than estimators from traditional regression models.
Recent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA) environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI) throughout early adulthood.
Methods and Findings
We used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study [n=4,092; Year 7 (24-42 years, 1992-1993) followed over 5 exams through Year 25 (2010-2011); 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population) and neighborhood development intensity (a composite density score). We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25th to 75th percentile) predicted inter-exam reduction in BMI of 0.09 kg/m2 [estimate (95% CI): -0.09 (-0.16, -0.02)]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m2 in men, with variation across other neighborhood features [estimate (95% CI) range: -0.14 (-0.29, 0.01) to -0.22 (-0.37, -0.08)]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m2 in men [estimate (95% CI) range: -0.23 (-0.39, -0.06) to -0.31 (-0.47, -0.15)] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI.
Findings suggest that improvements in neighborhood food retail or PA environments may accumulate to reduce BMI, but some neighborhood changes may be less beneficial to women.
Complex systems approaches have received increasing attention in public health because reductionist approaches yield limited insights in the context of dynamic systems. Most discussions to date have been highly abstract. There is a need to consider the application of complex systems approaches to specific research questions. After briefly reviewing the features of population health problems for which complex systems approaches are most likely to yield new insights, this commentary discusses possible applications of complex systems to health disparities research. It provides illustrative examples of how complex systems approaches may help address unanswered and persistent questions regarding genetic factors, life course processes, place effects, and the impact of upstream policies. It is argued that the concepts and methods of complex systems may help researchers move beyond current impasse points in health disparities research.
Background: Although research has shown that low socioeconomic status (SES) and minority communities have higher exposure to air pollution, few studies have simultaneously investigated the associations of individual and neighborhood SES with pollutants across multiple sites.
Objectives: We characterized the distribution of ambient air pollution by both individual and neighborhood SES using spatial regression methods.
Methods: The study population comprised 6,140 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Year 2000 annual average ambient PM2.5 and NOx concentrations were calculated for each study participant’s home address at baseline examination. We investigated individual and neighborhood (2000 U.S. Census tract level) SES measures corresponding to the domains of income, wealth, education, and occupation. We used a spatial intrinsic conditional autoregressive model for multivariable analysis and examined pooled and metropolitan area–specific models.
Results: A 1-unit increase in the z-score for family income was associated with 0.03-μg/m3 lower PM2.5 (95% CI: –0.05, –0.01) and 0.93% lower NOx (95% CI: –1.33, –0.53) after adjustment for covariates. A 1-SD–unit increase in the neighborhood’s percentage of persons with at least a high school degree was associated with 0.47-μg/m3 lower mean PM2.5 (95% CI: –0.55, –0.40) and 9.61% lower NOx (95% CI: –10.85, –8.37). Metropolitan area–specific results exhibited considerable heterogeneity. For example, in New York, high-SES neighborhoods were associated with higher concentrations of pollution.
Conclusions: We found statistically significant associations of SES measures with predicted air pollutant concentrations, demonstrating the importance of accounting for neighborhood- and individual-level SES in air pollution health effects research.
Citation: Hajat A, Diez-Roux AV, Adar SD, Auchincloss AH, Lovasi GS, O’Neill MS, Sheppard L, Kaufman JD. 2013. Air pollution and individual and neighborhood socioeconomic status: evidence from the Multi-Ethnic Study of Atherosclerosis (MESA). Environ Health Perspect 121:1325–1333; http://dx.doi.org/10.1289/ehp.1206337
In many studies, it has been hypothesized that stress and its biologic consequences may contribute to disparities in rates of cardiovascular disease. However, understanding of the most appropriate statistical methods to analyze biologic markers of stress, such as salivary cortisol, remains limited. The authors explore the utility of various statistical methods in modeling daily cortisol profiles in population-based studies. They demonstrate that the proposed methods allow additional insight into the cortisol profile compared with commonly used summaries of the profiles based on raw data. For instance, one can gain insights regarding the shape of the population average curve, characterize the types of individual-level departures from the average curve, and better understand the relation between covariates and attained cortisol levels or slopes at various points of the day, in addition to drawing inferences regarding common features of the cortisol profile, such as the cortisol awakening response and the area under the curve. The authors compare the inference and interpretations drawn from these methods and use data collected as part of the Multi-Ethnic Study of Atherosclerosis to illustrate them.
health disparities; parametric nonlinear models; salivary cortisol; semiparametric regression; stress response
Access to healthy foods has received increasing attention due to growing prevalence of obesity and diet-related health conditions yet there are major obstacles in characterizing the local food environment. This study developed a method to retrospectively characterize supermarkets for a single historic year, 2005, in 19 counties in 6 states in the USA using a supermarket chain-name list and two business databases. Data preparation, merging, overlaps, added-value amongst various approaches and differences by census tract area-level socio-demographic characteristics are described. Agreement between two food store databases was modest: 63%. Only 55% of the final list of supermarkets were identified by a single business database and selection criteria that included industry classification codes and sales revenue >=$2 million. The added-value of using a supermarket chain-name list and second business database was identification of an additional 14% and 30% of supermarkets, respectively. These methods are particularly useful to retrospectively characterize access to supermarkets during a historic period and when field observations are not feasible and business databases are used.
Residence characteristics; validity; reliability; food; geography; environment
It is often hypothesized that psychosocial stress may contribute to associations of socioeconomic position (SEP) with risk factors for cardiovascular disease (CVD). However, few studies have investigated this hypothesis among African Americans, who may be more frequently exposed to stressors due to social and economic circumstances. Cross-sectional data from the Jackson Heart Study (JHS), a large population-based cohort of African Americans, were used to examine the contributions of stressors to the association of SEP with selected cardiovascular (CVD) risk factors and subclinical atherosclerotic disease. Among women, higher income was associated with lower prevalence of hypertension, obesity, diabetes and carotid plaque and lower levels of stress. Higher stress levels were also weakly, albeit positively, associated with hypertension, diabetes, and obesity, but not with plaque. Adjustment for the stress measures reduced the associations of income with hypertension, diabetes and obesity by a small amount that was comparable to, or larger, than the reduction observed after adjustment for behavioral risk factors. In men, high income was associated with lower prevalence of diabetes and stressors were not consistently associated with any of the outcomes examined. Overall, modest mediation effects of stressors were observed for diabetes (15.9%), hypertension (9.7%), and obesity (5.1%) among women but only results for diabetes were statistically significant. No mediation effects of stressors were observed in men. Our results suggest that stressors may partially contribute to associations of SEP with diabetes and possibly hypertension and obesity in African American women. Further research with appropriate study designs and data is needed to understand the dynamic and interacting effects of stressors and behaviors on CVD outcomes as well as sex differences in these effects.
U.S.A.; Stress; social patterning; cardiovascular disease; risk factors; mediation analysis; African Americans
Little is known about neighborhood characteristics of workplaces, the extent to which they are independently and synergistically correlated with residential environments, and their impact on health.
This study investigated cross-sectional relationships between home and workplace neighborhood environments with body mass index (BMI) in 1,503 working participants of the Multi-Ethnic Study of Atherosclerosis (MESA) with mean age 59.6 (SD=7.4). Neighborhood features were socioeconomic status (SES), social environment (aesthetic quality, safety, and social cohesion), and physical environment (walking environment, recreational facilities, and food stores) derived from census data, locational data on businesses, and survey data. Paired t-tests and correlations compared environments overall and by distance between locations. Cross-classified multi-level models estimated associations with BMI.
Home neighborhoods had more favorable social environments while workplaces had more favorable SES and physical environments. Workplace and home measures were correlated (0.39–0.70) and differences between home and workplaces were larger as distance increased. Associations between BMI and neighborhood SES and recreational facilities were stronger for home environment (P≤0.05) but did not significantly differ for healthy food, safety, or social cohesion. Healthy food availability at home and work appeared to act synergistically (interaction P=0.01).
Consideration of workplace environment may enhance our understanding of how place affects BMI.
Neighborhood; Body Mass Index
The measurement of area-level attributes remains a major challenge in studies of neighborhood health effects. Even when neighborhood survey data are collected, they necessarily have incomplete spatial coverage. We investigated whether interpolation of neighborhood survey data was aided by information on spatial dependencies and supplementary data. Neighborhood “availability of healthy foods” was measured in a population-based survey of 5186 persons in Baltimore, New York, and Forsyth County (North Carolina). The following supplementary data were compiled from Census 2000 and InfoUSA, Inc.: distance to supermarkets, density of supermarkets and fruit and vegetable stores, housing density, distance to a high-income area, and percent of households that do not own a vehicle. We compared 4 interpolation models (ordinary least squares, residual kriging, spatial error regression, and thin-plate splines) using error statistics and Pearson correlation coefficients (r) from repeated replications of cross-validations. There was positive spatial autocorrelation in neighborhood availability of healthy foods (by site, Moran coefficient range = 0.10–0.28; all P < 0.0001). Prediction performances were generally similar for the evaluated models (r ≈ 0.35 for Baltimore and Forsyth; r ≈ 0.54 for New York). Supplementary data accounted for much of the spatial autocorrelation and, thus, spatial modeling was only advantageous when spatial correlation was at least moderate. A variety of interpolation techniques will likely need to be utilized in order to increase the data available for examining health effects of residential environments. The most appropriate method will vary depending on the construct of interest, availability of relevant supplementary data, and types of observed spatial patterns.
The relationship between poverty and tobacco consumption among adolescents has not been extensively studied, and what evidence exists has come almost entirely from developed countries. Moreover, the impact of contextual factors—such as school-level poverty—remains unclear.
We obtained information about smoking behavior from the Global Youth Tobacco Survey in Argentina in 2007. School-level characteristics were derived by matching schools to census areas from the 2001 Census. Additional school-level information was obtained from the Ministry of Education. Random intercept models were used to evaluate the associations of school-level variables (poverty in the census area of the school, school receipt of social assistance, and public or private status) with current smoking, intention to quit, secondhand smoke exposure outside the home, support for smoke-free laws, purchase of single cigarettes among smokers, and susceptibility to smoking in 5 years among nonsmokers.
After controlling for age and sex, students attending schools receiving social assistance were more likely to smoke (odds ratio [OR] 1.35, 95% CI 1.02–1.80) and to purchase loose cigarettes (OR 1.66, 95% CI 1.08–2.54), whereas school poverty was significantly associated with secondhand smoke exposure (OR 1.27, 95% CI 1.04–1.58).
This study shows that an association exists between unfavorable contextual school characteristics and tobacco consumption and related measures among youth in Argentina. Efforts to prevent smoking may need to address the school-level factors that place youth at higher risk.
Coronary heart disease (CHD) mortality is one of the major contributors to racial disparities in health in the United States (US). We examined spatial heterogeneity in black–white differences in CHD mortality across the US and assessed the contributions of poverty and segregation. We used county-level, age-adjusted CHD mortality rates for blacks and whites in the continental US between 1996 and 2006. Geographically weighted regression was employed to assess spatial heterogeneity. There was significant spatial heterogeneity in black–white differences in CHD mortality (median black–white difference 17.7 per 100,000, 25th–75th percentile (IQR): 4.0, 34.0, P value for spatial non-stationarity < 0.0001) before controlling for poverty and segregation. This heterogeneity was no longer present after accounting for county differences in race-specific poverty and segregation and interactions of these variables with race (median black–white difference −13.5 per 100,000, IQR: −41.3, 15.7, P value for spatial non-stationarity = 0.4346). The results demonstrate the importance of spatial heterogeneity in understanding and eliminating racial disparities in CHD mortality. Additional research to identify the individual and contextual factors that explain the local variations in racial disparities is warranted.
Racial disparities; CHD mortality; Poverty; Segregation; Spatial heterogeneity; Geographically weighted regression; United States
Scientific and policy interest in health disparities, defined as systematic, plausibly avoidable health differences adversely affecting socially disadvantaged groups, has increased markedly over the past few decades. Like other research, research in health disparities is strongly influenced by the underlying conceptual model of the hypothetical causes of disparities. Conceptual models are important and a major source of debate because multiple types of factors and processes may be involved in generating disparities, because different disciplines emphasize different types of factors, and because the conceptual model often drives what is studied, how results are interpreted, and which interventions are identified as most promising. This article reviews common conceptual approaches to health disparities including the genetic model, the fundamental cause model, the pathways model, and the interaction model. Strengths and limitations of the approaches are highlighted. The article concludes by outlining key elements and implications of an integrative systems-based conceptual model.
health inequalities; social determinants; systems
There is growing interest in understanding how food environments affect diet, but characterizing the food environment is challenging. The authors investigated the relation between global diet measures (an empirically derived “fats and processed meats” (FPM) dietary pattern and the Alternate Healthy Eating Index (AHEI)) and three complementary measures of the local food environment: 1) supermarket density, 2) participant-reported assessments, and 3) aggregated survey responses of independent informants. Data were derived from the baseline examination (2000–2002) of the Multi-Ethnic Study of Atherosclerosis, a US study of adults aged 45–84 years. A healthy diet was defined as scoring in the top or bottom quintile of AHEI or FPM, respectively. The probability of having a healthy diet was modeled by each environment measure using binomial regression. Participants with no supermarkets near their homes were 25–46% less likely to have a healthy diet than those with the most stores, after adjustment for age, sex, race/ethnicity, and socioeconomic indicators: The relative probability of a healthy diet for the lowest store density category versus the highest was 0.75 (95% confidence interval: 0.59, 0.95) for the AHEI and 0.54 (95% confidence interval: 0.42, 0.70) for FPM. Similarly, participants living in areas with the worst-ranked food environments (by participants or informants) were 22–35% less likely to have a healthy diet than those in the best-ranked food environments. Efforts to improve diet may benefit from combining individual and environmental approaches.
diet; food; residence characteristics; social class
The purpose of this study was to examine the social patterning of cumulative dysregulation of multiple systems, or allostatic load (AL), among African Americans adults.
We examined the cross-sectional associations of socioeconomic status (SES) with summary indices of allostatic load and neuroendocrine, metabolic, autonomic, and immune function components in 4,048 Jackson Heart Study participants.
Lower education and income were associated with higher AL scores in African American women and men. Patterns were most consistent for the metabolic and immune dimensions, less consistent for the autonomic dimension and absent for the neuroendocrine dimension among African American women. Associations of SES with the global AL score and the metabolic and immune domains persisted after adjustment for behavioral factors and were stronger for income than education. There was some evidence that the neuroendocrine dimension was inversely associated with SES after behavioral adjustment in men, but the immune and autonomic components did not show clear dose response trends and no associations were observed for the metabolic component.
Findings support the hypothesis that AL is socially patterned by SES in African American women, but less consistently in African American men.
Walking distance is an important concept in the fields of transportation and public health. A distance of 0.25 miles is often used as an acceptable walking distance in U.S. research studies. Overall, research on the distance and duration of walking trips for different purposes and across different population groups remains limited.
This study examines the prevalence of walking and distances and durations of walking trips for different purposes among U.S. residents.
The distances and durations of walking trips for different purposes across population groups were compared using nationally representative data from the 2009 National Household Travel Survey (NHTS). Distance decay functions were used to summarize the distribution of walking distances and durations for different purposes and population subgroups. Data were analyzed in 2011.
Sixteen percent of respondents had at least one daily walking trip. The mean and median values for walking distance were 0.7 and 0.5 miles, respectively. For walking duration, the mean and median values were 14.9 and 10 minutes. About 65% of walking trips were more than 0.25 miles, and about 18% of walking trips were more than 1 mile. Large variations were found among various purposes for both distance and duration. The distances and durations of walking for recreation were substantially longer than those for other purposes. People with lower versus higher household income walked longer distances for work but shorter distances for recreation.
Only a small fraction of respondents walk, but trips longer than 0.25 miles are common. There is substantial variability in the distance and duration of walking trips by purpose and population subgroups. These differences have implications for developing strategies to increase physical activity through walking.
Despite the multiple advantages of active travel to school, only a small percentage of US children and adolescents walk or bicycle to school. Intervention studies are in a relatively early stage and evidence of their effectiveness over long periods is limited. The purpose of this study was to illustrate the utility of agent-based models in exploring how various policies may influence children’s active travel to school.
An agent-based model was developed to simulate children’s school travel behavior within a hypothetical city. The model was used to explore the plausible implications of policies targeting two established barriers to active school travel: long distance to school and traffic safety. The percent of children who walk to school was compared for various scenarios.
To maximize the percent of children who walk to school the school locations should be evenly distributed over space and children should be assigned to the closest school. In the case of interventions to improve traffic safety, targeting a smaller area around the school with greater intensity may be more effective than targeting a larger area with less intensity.
Despite the challenges they present, agent based models are a useful complement to other analytical strategies in studying the plausible impact of various policies on active travel to school.
Neighborhood-level interventions provide an opportunity to better understand the impact that neighborhoods have on health. In 2004, municipal authorities in Medellín, Colombia, built a public transit system to connect isolated low-income neighborhoods to the city’s urban center. Transit-oriented development was accompanied by municipal investment in neighborhood infrastructure. In this study, the authors examined the effects of this exogenous change in the built environment on violence. Neighborhood conditions and violence were assessed in intervention neighborhoods (n = 25) and comparable control neighborhoods (n = 23) before (2003) and after (2008) completion of the transit project, using a longitudinal sample of 466 residents and homicide records from the Office of the Public Prosecutor. Baseline differences between these groups were of the same magnitude as random assignment of neighborhoods would have generated, and differences that remained after propensity score matching closely resembled imbalances produced by paired randomization. Permutation tests were used to estimate differential change in the outcomes of interest in intervention neighborhoods versus control neighborhoods. The decline in the homicide rate was 66% greater in intervention neighborhoods than in control neighborhoods (rate ratio = 0.33, 95% confidence interval: 0.18, 0.61), and resident reports of violence decreased 75% more in intervention neighborhoods (odds ratio = 0.25, 95% confidence interval 0.11, 0.67). These results show that interventions in neighborhood physical infrastructure can reduce violence.
causality; economic development; environment; neighborhood; residence characteristics; violence
A major challenge in studies of the impact of the local food environment is the accuracy of measures of healthy food access. The authors assessed agreement between self-reported and directly measured availability of healthful choices within neighborhood food stores and examined the validity of reported availability using directly measured availability as a “gold standard.” Reported availability was measured via a phone survey of 1,170 adults in Baltimore, Maryland, in 2004. Directly measured availability was assessed in 226 food stores in 2006 using a modified Nutrition Environment Measures Survey in Stores (NEMS-S). Whites, college-educated individuals, and higher income households (≥$50,000) had significantly higher reported and directly measured availability than did blacks, those with less education, and lower income households. Persons in areas with above average directly measured availability reported above average availability 70%–80% of the time (sensitivity = 79.6% for all stores within 1 mile (1.6 km) of participants’ homes and 69.6% for the store with the highest availability within 1 mile). Those with below average directly measured availability reported low availability only half the time. With revisions to improve specificity, self-reported measures can be reasonable indicators of healthy food availability and provide feasible proxy measures of directly assessed availability.
food; reproducibility of results; residence characteristics; self report; validity (epidemiology)
Subjective social status has been shown to be inversely associated with multiple cardiovascular risk factors, independent of objective social status. However, few studies have examined this association among African Americans and the results have been mixed. Additionally, the influence of discrimination on this relationship has not been explored. Using baseline data (2000–2004) from the Jackson Heart Study, an African American cohort from the U.S. South (N = 5301), we quantified the association of subjective social status with selected cardiovascular risk factors: depressive symptoms, perceived stress, waist circumference, insulin resistance and prevalence of diabetes. We contrasted the strength of the associations of these outcomes with subjective versus objective social status and examined whether perceived discrimination confounded or modified these associations. Subjective social status was measured using two 10-rung "ladders," using the U.S. and the community as referent groups. Objective social status was measured using annual family income and years of schooling completed. Gender-specific multivariable linear and logistic regression models were fit to examine associations. Subjective and objective measures were weakly positively correlated. Independent of objective measures, subjective social status was significantly inversely associated with depressive symptoms (men and women) and insulin resistance (women). The associations of subjective social status with the outcomes were modest and generally similar to the objective measures. We did not find evidence that perceived racial discrimination strongly confounded or modified the association of subjective social status with the outcomes. Subjective social status was related to depressive symptoms but not consistently to stress or metabolic risk factors in African Americans.
USA; African American; subjective social status; cardiovascular; risk factors
Low dietary quality is a key contributor to obesity and related illnesses, and lower income is generally associated with worse dietary profiles. The unequal geographic distribution of healthy food resources could be a key contributor to income disparities in dietary profiles.
To explore the role that economic segregation can have in creating income differences in healthy eating and to explore policy levers that may be appropriate for countering income disparities in diet.
A simple agent-based model was used to identify segregation patterns that generate income disparities in diet. The capacity for household food preferences and relative pricing of healthy foods to overcome or exacerbate the differential was explored.
Absent other factors, income differentials in diet resulted from the segregation of high-income households and healthy food stores from low-income households and unhealthy food stores. When both income groups shared a preference for healthy foods, low-income diets improved but a disparity remained. Both favorable preferences and relatively cheap healthy foods were necessary to overcome the differential generated by segregation.
The model underscores the challenges of fostering favorable behavior change when people and resources are residentially segregated and behaviors are motivated or constrained by multiple factors. Simulation modeling can be a useful tool for proposing and testing policies or interventions that will ultimately be implemented in a complex system where the consequences of multidimensional interactions are difficult to predict.
Despite the growing burden of chronic disease globally, few studies have examined the socioeconomic patterning of risk across countries. The authors examined differences in the social patterning of body mass index (BMI) and current smoking by urbanicity among 70 countries from the 2002–2003 World Health Surveys. Age-adjusted, gender-stratified ordinary least squares and logistic regression analyses were conducted in each country to assess the relation between education and BMI or smoking. Meta-analytic techniques were used to assess heterogeneity between countries in the education-risk factor relations. Meta-regression was used to determine whether the heterogeneity could be explained by country-level urbanicity. In the least urban countries, persons with higher education had a higher BMI, while the opposite pattern was seen in the most urban countries, with this pattern being especially pronounced among women. In contrast, smoking was consistently concentrated among persons of lower education among all men and among women in the least urban countries. For women in the most urban countries, higher education was associated with higher odds of smoking, although there was substantial variability in this relation. These results highlight a global trend toward an increasing burden of chronic disease risk among persons of lower socioeconomic position as countries become more urban.
body mass index; smoking; socioeconomic factors; urbanization
Epigenetic changes are a potential mechanism contributing to race/ethnic and socioeconomic disparities in health. However, there is scant evidence of the race/ethnic and socioeconomic patterning of epigenetic marks. We used data from the Multi-Ethnic Study of Atherosclerosis Stress Study (N = 988) to describe age- and gender- independent associations of race/ethnicity and socioeconomic status (SES) with methylation of Alu and LINE-1 repetitive elements in leukocyte DNA. Mean Alu and Line 1 methylation in the full sample were 24% and 81% respectively. In multivariable linear regression models, African-Americans had 0.27% (p<0.01) and Hispanics 0.20% (p<0.05) lower Alu methylation than whites. In contrast, African-Americans had 0.41% (p<0.01) and Hispanics 0.39% (p<0.01) higher LINE-1 methylation than whites. These associations remained after adjustment for SES. In addition, a one standard deviation higher wealth was associated with 0.09% (p<0.01) higher Alu and 0.15% (p<0.01) lower LINE-1 methylation in age- and gender- adjusted models. Additional adjustment for race/ethnicity did not alter this pattern. No associations were observed with income, education or childhood SES. Our findings, from a large community-based sample, suggest that DNA methylation is socially patterned. Future research, including studies of gene-specific methylation, is needed to understand better the opposing associations of Alu and LINE-1 methylation with race/ethnicity and wealth as well as the extent to which small methylation changes in these sequences may influence disparities in health.
We use an exploratory agent-based model of adults’ walking behavior within a city to examine the possible impact of interventions on socioeconomic differences in walking. Simulated results show that for persons of low socioeconomic status, increases in walking resulting from increases in their positive attitude towards walking may diminish over time if other features of the environment are not conducive to walking. Similarly, improving the safety level for the lower SES neighborhoods may be effective in increasing walking, however, the magnitude of its effectiveness varies by levels of land use mix, such that effects of safety are greatest when persons live in areas with a large mix of uses.
agent-based model; walking; socioeconomic status