Although specific measurement instruments are necessary to better understand the relationship between features of neighborhoods and health, very few studies have developed instruments to measure neighborhood features in developing countries. The objective of the study was to develop valid and reliable measures of neighborhood context useful in a Latin American urban context, assess their psychometric and ecometric properties, and examine individual and neighborhood-level predictors of these measures. We analyzed data from a multistage household survey (2008–2009) conducted in Belo Horizonte City by the Observatory for Urban Health. One adult in each household was selected to answer a questionnaire that included scales to measure neighborhood domains. Census tracts were used to proxy neighborhoods. Internal consistency was evaluated by Cronbach’s alpha, and multilevel models were used to estimate ecometric properties and to estimate associations of neighborhood measures with socioeconomic indicators. The final sample comprised 4048 survey respondents representing 149 census tracts. We assessed ten neighborhood environment dimensions: public services, aesthetic quality, walking environment, safety, violence, social cohesion, neighborhood participation, neighborhood physical disorder, neighborhood social disorder, and neighborhood problems. Cronbach’s alpha coefficients ranged from 0.53 to 0.83; intraneighborhood correlations ranged from 0.02 to 0.53, and neighborhood reliability varied from 0.76 to 0.99. Most scales were associated with individual and neighborhood socioeconomic predictors. Questionnaires can be used to reliably measure neighborhood contexts in developing countries.
Epidemiologic methods; Psychometrics; Residence characteristics; Data collection; Self-report; Environment design; Censuses
Depression is a heritable trait that exists on a continuum of varying severity and duration. Yet, the search for genetic variants associated with depression has had few successes. We exploit the entire continuum of depression to find common variants for depressive symptoms.
In this genome-wide association study, we combined the results of 17 population-based studies assessing depressive symptoms with the Center for Epidemiological Studies Depression Scale. Replication of the independent top hits (p < 1 × 10−5) was performed in five studies assessing depressive symptoms with other instruments. In addition, we performed a combined meta-analysis of all 22 discovery and replication studies.
The discovery sample comprised 34,549 individuals (mean age of 66.5) and no loci reached genome-wide significance (lowest p = 1.05 × 10−7). Seven independent single nucleotide polymorphisms were considered for replication. In the replication set (n = 16,709), we found suggestive association of one single nucleotide polymorphism with depressive symptoms (rs161645, 5q21, p = 9.19 × 10−3). This 5q21 region reached genome-wide significance (p = 4.78 × 10−8) in the overall meta-analysis combining discovery and replication studies (n = 51,258).
The results suggest that only a large sample comprising more than 50,000 subjects may be sufficiently powered to detect genes for depressive symptoms.
Center for Epidemiologic Studies Depression Scale; CHARGE consortium; depression; depressive symptoms; genetics; genome-wide association study; meta-analysis
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.
Individuals living in primary care health professional shortage areas (PC-HPSA) often have difficulty obtaining medical care; however, no previous studies have examined association of PC-HPSA residence with prevalence of CVD risk factors.
Methods and Results
To examine this question, the authors used data from the Multi-Ethnic Study of Atherosclerosis baseline exam (2000–2002). Outcomes included the prevalence of diabetes, hypertension, hyperlipidemia, smoking and obesity as well as the awareness and control of diabetes, hypertension, and hyperlipidemia. Multivariable Poisson models were used to examine the independent association of PC-HPSA residence with each outcome. Models were sequentially adjusted for demographics, acculturation, socioeconomic status, access to health care and neighborhood socioeconomic status. Similar to the national average, 16.7% of MESA participants lived in a PC-HPSA. In unadjusted analyses, prevalence rates of diabetes (14.8% vs 11.0%), hypertension (48.2% vs 43.1%), obesity (35.7% vs 31.1%) and smoking (15.5% vs 12.1%) were significantly higher among residents of PC-HPSAs. There were no significant differences in the awareness or control of diabetes, hypertension, or hyperlipidemia. After adjustment, residence in a PC-HPSA was not independently associated with CVD risk factor prevalence, awareness or control.
This study suggests that increased prevalence of CVD risk factors in PC-HPSAs are explained by the demographic and socioeconomic characteristics of their residents. Future interventions aimed at increasing the number of primary care physicians may not improve cardiovascular risk without first addressing other factors underlying healthcare disparities.
epidemiology; prevention; risk factors
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
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
While behavioral change is necessary to reverse the obesity epidemic, it can be difficult to achieve and sustain in unsupportive residential environments. This study hypothesized that environmental resources supporting walking and a healthy diet are associated with reduced obesity incidence. Data came from 4008 adults aged 45–84 at baseline who participated in a neighborhood ancillary study of the Multi-Ethnic Study of Atherosclerosis. Participants were enrolled at 6 study sites at baseline (2000–2002) and neighborhood scales were derived from a supplementary survey that asked community residents to rate availability of healthy foods and walking environments for a one-mile buffer area. Obesity was defined as body mass index (BMI) >=30 kg/m2. Associations between incident obesity and neighborhood exposure were examined using proportional hazards and generalized linear regression. Among 4008 non-obese participants, 406 new obesity cases occurred during 5 years of follow-up. Neighborhood healthy food environment was associated with 10% lower obesity incidence per standard deviation increase neighborhood score. The association persisted after adjustment for baseline BMI and individual level covariates (HR 0.88, 95% CI: 0.79, 0.97), and for correlated features of the walking environment but confidence intervals widened to include the null (HR 0.89, 95% CI: 0.77, 1.03). Associations between neighborhood walking environment and lower obesity were weaker and did not persist after adjustment for correlated neighborhood healthy eating amenities (HR 0.98, 95% CI 0.84, 1.15). Altering the residential environment so that healthier behaviors and lifestyles can be easily chosen may be a pre-condition for sustaining existing healthy behaviors and for adopting new healthy behaviors.
Adult; Health Behavior; Obesity/*epidemiology; Residence Characteristics; Longitudinal Studies; Geographic Information Systems; Environment Design; Public Health; Risk Factors
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
Neighborhood characteristics, such as healthy food availability, have been associated with consumption of healthy food. Little is known about the influence of the local food environment on other dietary choices, such as the decision to consume organic food. We analyzed the associations between organic produce consumption and demographic, socioeconomic and neighborhood characteristics in 4,064 participants aged 53–94 in the Multi-Ethnic Study of Atherosclerosis using log-binomial regression models. Participants were classified as consuming organic produce if they reported eating organic fruits and vegetables either “sometimes” or “often or always”. Women were 21% more likely to consume organic produce than men (confidence interval [CI]: 1.12–1.30), and the likelihood of organic produce consumption was 13% less with each additional 10 years of age (CI: 0.84–0.91). Participants with higher education were significantly more likely to consume organic produce (prevalence ratios [PR] were 1.05 with a high school education, 1.39 with a bachelor's degree and 1.68 with a graduate degree, with less than high school as the reference group [1.00]). Per capita household income was marginally associated with produce consumption (p = 0.06), with the highest income category more likely to consume organic produce. After adjustment for these individual factors, organic produce consumption was significantly associated with self-reported assessment of neighborhood produce availability (PR: 1.07, CI: 1.02–1.11), with an aggregated measure of community perception of the local food environment (PR: 1.08, CI: 1.00–1.17), and, to a lesser degree, with supermarket density (PR: 1.02: CI: 0.99–1.05). This research suggests that both individual-level characteristics and qualities of the local food environment are associated with having a diet that includes organic food.
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
Concentrations of outdoor fine particulate matter (PM2.5) have been associated with cardiovascular disease. PM2.5 chemical composition may be responsible for effects of exposure to PM2.5.
Using data from the Multi-Ethnic Study of Atherosclerosis (MESA) collected in 2000–2002 on 6,256 US adults without clinical cardiovascular disease in six U.S. metropolitan areas, we investigated cross-sectional associations of estimated long-term exposure to total PM2.5 mass and PM2.5 components (elemental carbon [EC], organic carbon [OC], silicon and sulfur) with measures of subclinical atherosclerosis (coronary artery calcium [CAC] and right common carotid intima-media thickness [CIMT]). Community monitors deployed for this study from 2007 to 2008 were used to estimate exposures at baseline addresses using three commonly-used approaches: (1) nearest monitor (the primary approach), (2) inverse-distance monitor weighting and (3) city-wide average.
Using the exposure estimate based on nearest monitor, in single-pollutant models, increased OC (effect estimate [95% CI] per IQR: 35.1 μm [26.8, 43.3]), EC (9.6 μm [3.6,15.7]), sulfur (22.7 μm [15.0,30.4]) and total PM2.5 (14.7 μm [9.0,20.5]) but not silicon (5.2 μm [−9.8,20.1]), were associated with increased CIMT; in two-pollutant models, only the association with OC was robust to control for the other pollutants. Findings were generally consistent across the three exposure estimation approaches. None of the PM measures were positively associated with either the presence or extent of CAC. In sensitivity analyses, effect estimates for OC and silicon were particularly sensitive to control for metropolitan area.
Employing commonly-used exposure estimation approaches, all of the PM2.5 components considered, except silicon, were associated with increased CIMT, with the evidence being strongest for OC; no component was associated with increased CAC. PM2.5 chemical components, or other features of the sources that produced them, may be important in determining the effect of PM exposure on atherosclerosis. These cross-sectional findings await confirmation in future work employing longitudinal outcome measures and using more sophisticated approaches to estimating exposure.
Atherosclerosis; Cardiovascular diseases; Coronary artery disease; Air pollution; Particulate matter